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Bala, A., Malhotra, S., Gupta, N., & Ahuja, N. (2016). Emerging Green ICT: Heart Disease Prediction Model in Cloud Environment. In Proceedings of International Conference on ICT for Sustainable Development (pp. 579-587). Springer Singapore. |
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Turabieh, H. (2016). A Hybrid ANN-GWO Algorithm for Prediction of Heart Disease. American Journal of Operations Research, 6(02), 136. |
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3 |
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Karlik, B. The Positive Effects of Fuzzy C-Means Clustering on Supervised Learning Classifiers. |
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Ruiz-Fernández, D., Torra, A. M., Soriano-Payá, A., Marín-Alonso, O., & Palencia, E. T. (2016). Aid decision algorithms to estimate the risk in congenital heart surgery. Computer Methods and Programs in Biomedicine. |
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5 |
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Pant, H., & Srivastava, R. MINDEX_IB: A Feature Selection method for Imbalanced Dataset. IONOSPHERE, 34(2), 126-225. |
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6 |
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Patil, N., Patil, A. S., & Pawar, B. V. (2016). Survey of Named Entity Recognition Systems with respect to Indian and Foreign Languages. International Journal of Computer Applications, 134(16). |
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7 |
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Elyazgi, M., Nilashi, M., Ibrahim, O., Rayhan, A., & Elyazgi, S. (2016). Evaluating the Factors Influencing E-book Technology Acceptance among School Children Using TOPSIS Technique. Journal of Soft Computing and Decision Support Systems, 3(2), 11-25. |
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8 |
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Chitra, D., & Nasira, G. M. (2015). wrapper based feature selection for ct image. ictact journal on image & video processing, 6(1). |
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Pyshkin, E., & Kuznetsov, A. (2015, September). Approach to building a web-based expert system interface and its application for software provisioning in clouds. In Computer Science and Information Systems (FedCSIS), 2015 Federated Conference on (pp. 343-354). IEEE. |
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10 |
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Radhimeenakshi, S., & Nasira, G. M. Prediction of Heart Disease using Neural Network with Back Propagation. |
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11 |
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Bilgi, N. B. (2015). A Rule–Based Graphical Decision Charting Approach to Legal Knowledge Based System. In Logic in the Theory and Practice of Lawmaking (pp. 435-457). Springer International Publishing. |
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12 |
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Elyazgi, M., Nilashi, M., Ibrahim, O., Rayhan, A., & Elyazgi, S. (2015). Journal of Soft Computing and Decision Support Systems. Journal of Soft Computing and Decision, 2(5). |
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13 |
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Wei, the staff super, & SOCIALIST. (2015). Applied Research in nonlinear control arm of linear quadratic regulator. Journal of Mechanical & Electrical Engineering, 32 (6). |
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14 |
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Nilashi, M., Ahmadi, H., Ahani, A., & Ibrahim, O. (2015). Evaluating the Factors Affecting Adoption of Hospital Information System Using Analytic Hierarchy Process. Journal of Soft Computing and Decision Support Systems, 3(1), 8-35. |
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15 |
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Babakhani, A. R., Moradi, E., Salooki, M., & Fakhraie, R. (2015). Novel Intelligent-Based Gravity Control for Industrial Robot Arm. International Journal of Hybrid Information Technology, 8(1), 121-132. |
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16 |
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Ulagapriya, S., & Balasubramanian, P. (2015, August). Study on inter sector association rules in national stock exchange, India. In Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on (pp. 859-865). IEEE. |
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17 |
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Maatallah, M., & Seridi-Bouchelaghem, H. (2015). A fuzzy hybrid approach to enhance diversity in top-N recommendations. International Journal of Business Information Systems, 19(4), 505-530. |
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18 |
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Kurniawan, K. A., Utomo, D., & Nugroho, S. (2015). Direction Control System on a Carrier Robot Using Fuzzy Logic Controller. In Intelligence in the Era of Big Data (pp. 27-36). Springer Berlin Heidelberg. |
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19 |
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Helwan, A. (2015). Heart Attack Prediction System Based Neural Arbitration. Turkish Online Journal of Science & Technology, 5(2). |
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20 |
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Purnamawati, M. M. D., Santoso, A. J., & Ardanari, P. (2015, July). perancangan sistem pakar neuro fuzzy untuk pengenalan tokoh wayang kulit purwa. In Seminar Nasional Informatika 2008 (Vol. 1, No. 4). |
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21 |
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Katiyar, V. (2015). Relative Performance of Certain Meta Heuristics on Vehicle Routing Problem with Time Windows. International Journal of Information Technology and Computer Science (IJITCS), 7(12), 40. |
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22 |
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Han, Z. (2015). Truckload Carrier Selection, Routing and Cost Optimization. |
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23 |
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Johar, F., Potts, C., & Bennell, J. (2015). Vehicle Routing Problem with Time Constraints. Malaysian Journal of Fundamental and Applied Sciences, 11(4). |
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MUYIWA, O., FABOYE, I., & OGUNSHIPE, B. (2015). Development of case based ailment diagnoses nutrition prescription expert system. American International Journal of Contemporary Scientific Research, 2(6), 62-68. |
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25 |
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Moses, D. (2015). A survey of data mining algorithms used in cardiovascular disease diagnosis from multi-lead ECG data. Kuwait Journal of Science, 42(2). |
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26 |
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Shahangian, B., & Pourghassem, H. (2015). Automatic brain hemorrhage segmentation and classification algorithm based on weighted grayscale histogram feature in a hierarchical classification structure. Biocybernetics and Biomedical Engineering. |
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27 |
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Pant, H., & Srivastava, R. a survey on feature selection methods for imbalanced datasets. |
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28 |
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Rosmalina, A. R. Forecasting export price of sabah sawn timber using neural network. |
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29 |
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Khosravi, B., Pourahmad, S., Bahreini, A., Nikeghbalian, S., & Mehrdad, G. (2015). Five Years Survival of Patients After Liver Transplantation and Its Effective Factors by Neural Network and Cox Poroportional Hazard Regression Models. Hepatitis monthly, 15(9). |
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30 |
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Amarappa, S., & Sathyanarayana, S. V. kannada named entity recognition and classification (nerc) based on multinomial naïve bayes (mnb) classifier. |
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31 |
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Srikanth, K., & Arivazhagan, D. Prediction Model to Enhance Resource Efficiently For Hospitals. |
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32 |
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Akbarzadeh-T, M. R., & Bashari, M. RLS Based Adaptive IVT2 Fuzzy Controller for Uncertain Model of Inverted Pendulum. |
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33 |
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Ranjbar, B., Mahmoodi, J., Karbasi, H., Dashti, G., & Omidvar, A. (2015). Robot Manipulator Path Planning Based on Intelligent Multi-resolution Potential Field. International Journal of u-and e-Service, Science and Technology, 8(1), 11-26. |
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34 |
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sadegh Dahideh, M., Najafi, M., Zarei, A., Barmayeh, Y., & Afshar, M. (2015). Intelligent Mechatronic Model Reference Theory for Robot End-effector Control. International Journal of u-and e-Service, Science and Technology, 8(1), 165-172. |
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35 |
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Sahamijoo, G., Avatefipour, O., Nasrabad, M. R. S., Taghavi, M., & Piltan, F. (2015). Research on Minimum Intelligent Unit for Flexible Robot. International Journal of Advanced Science and Technology, 80, 79-104. |
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36 |
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Das, B. R., Patnaik, S., Baboo, S., & Dash, N. S. (2015). A System for Recognition of Named Entities in Odia Text Corpus Using Machine Learning Algorithm. In Computational Intelligence in Data Mining-Volume 1 (pp. 315-324). Springer India. |
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37 |
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Freiberg, M. Knowledge-Based-System Usability. |
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38 |
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Chahkoutahi, A., MoradiPour, M. R., Gholami, M., Ashja, S., & Rahimi, M. H. (2015). Design High Precision Intelligent Nonlinear-Based Controller. International Journal of u-and e-Service, Science and Technology, 8(1), 201-210. |
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39 |
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Prerana, P. S. (2015). Comparative Study of GD, LM and SCG Method of Neural Network for Thyroid Disease Diagnosis. IJAR, 1(10), 34-39. |
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40 |
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Ross, O. H. M., & Cruz, R. S. (2015). Evolving Embedded Fuzzy Controllers. In Springer Handbook of Computational Intelligence (pp. 1451-1477). Springer Berlin Heidelberg. |
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41 |
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Abdullah, N., Tiew, Y. W., & Rosmalina, A. R. Export price of sabah sawn timber: now and future? a mathematical approach using neural network. |
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42 |
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ORESKI, D., & KLICEK, B. A novel feature selection techniques based on contrast set mining. |
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43 |
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Pathak, A., Agarwal, T., & Mohan, A. (2015). A Novel Fuzzy Membership Partitioning for Improved Voting in Fault Tolerant System. Journal of Intelligent Learning Systems and Applications, 7(01), 1. |
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44 |
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Mirsaeidi, M., & Karimi, A. (2015). A novel probabilistic bit voter using genetic algorithm for fault-tolerant systems. International Journal of Computer Science Issues (IJCSI), 12(4), 88. |
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45 |
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Ceylan, R., Özbay, Y., & Karlik, B. (2014). comparison of type-2 fuzzy clustering-based cascade classifier models for ecg arrhythmias. biomedical engineering: applications, basis and communications, 26(06), 1450075. |
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46 |
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Bazregar, M., Piltan, F., Nabaee, A., & Ebrahimi, M. (2014). Design Modified Fuzzy PD Gravity Controller with Application to Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 6(3), 82. |
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47 |
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Lam, H. K., Li, H., Deters, C., Secco, E. L., Wurdemann, H. A., & Althoefer, K. (2014). Control design for interval type-2 fuzzy systems under imperfect premise matching. Industrial Electronics, IEEE Transactions on, 61(2), 956-968. |
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48 |
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Mozafari, N. G., Piltan, F., Shamsodini, M., Yazdanpanah, A., & Roshanzamir, A. (2014). On Line Tuning Premise and Consequence FIS Based on Lyaponuv Theory with Application to Continuum Robot. International Journal of Intelligent Systems and Applications (IJISA), 6(3), 96. |
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49 |
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Nazari, I., Hosainpour, A., Piltan, F., Emamzadeh, S., & Mirzaie, M. (2014). Design Sliding Mode Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 6(4), 63. |
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50 |
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Piran, M., Piltan, F., Akbari, M., Garg, R., & Bazregar, M. (2014). Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine. International Journal of Intelligent Systems and Applications (IJISA), 6(2), 76. |
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51 |
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Nazemizadeh, M., Taheri, M., & Nazeri, S. (2014). THE APPLICATION OF FUZZY-LOGIC METHOD TO CONTROL OF ROBOTS: A REVIEW STUDY. International Journal of Mechanical Engineering and Robotics Research, 3(2), 229. |
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52 |
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Mohan, K. R., Paramasivam, I., & Narayan, S. S. (2014, February). Prediction and Diagnosis of Cardio Vascular Disease--A Critical Survey. In Computing and Communication Technologies (WCCCT), 2014 World Congress on (pp. 246-251). IEEE. |
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53 |
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Leskelä, C. L. H. (2014). Learning for RoboCup Soccer. |
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54 |
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Ðordevic, m. z. klasifikacija srcanih oboljenja pomocu neuronskih mreta classification of heart diseases using neural networks. |
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55 |
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Shahangian, B., Pourghassem, H., B. Shahngyan, & Hussein Pourghassem. Automatic detection and classification using Support Vector Machine multi-class areas of brain hemorrhage on CT images. Journal of Medicine, 32 (284), 631-646. |
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56 |
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Krenek, J., & Kuca, K. Artificial Neural Data M. |
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57 |
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Mozafari, N. G., Piltan, F., Shamsodini, M., Yazdanpanah, A., & Roshanzamir, A. (2014). On Line Tuning Premise and Consequence FIS Based on Lyaponuv Theory with Application to Continuum Robot. International Journal of Intelligent Systems and Applications (IJISA), 6(3), 96. |
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58 |
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Krenek, J., Kuca, K., Krejcar, O., Maresova, P., Sobeslav, V., & Blazek, P. (2014, November). Artificial neural network tools for computerised data modeling and processing. In Computational Intelligence and Informatics (CINTI), 2014 IEEE 15th International Symposium on (pp. 255-260). IEEE. |
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59 |
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Maheta, H. H., & Dabhi, V. K. (2014, February). An improved SPEA2 Multi objective algorithm with non dominated elitism and Generational Crossover. In Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on (pp. 75-82). IEEE. |
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60 |
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Bouaiachi, Y., Khaldi, M., & Azmani, A. (2014, October). Neural network-based decision support system for pre-diagnosis of psychiatric disorders. In Information Science and Technology (CIST), 2014 Third IEEE International Colloquium in (pp. 102-106). IEEE. |
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61 |
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Latifi, Z., & Karimi, A. (2014). A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot. Procedia Computer Science, 42, 301-307. |
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62 |
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Nazari, I., Hosainpour, A., Piltan, F., Emamzadeh, S., & Mirzaie, M. (2014). Design Sliding Mode Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 6(4), 63. |
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63 |
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Piran, M., Piltan, F., Akbari, M., Garg, R., & Bazregar, M. (2014). Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine. International Journal of Intelligent Systems and Applications (IJISA), 6(2), 76. |
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64 |
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Bazregar, M., Piltan, F., Nabaee, A., & Ebrahimi, M. (2014). Design Modified Fuzzy PD Gravity Controller with Application to Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 6(3), 82. |
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65 |
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El-Nagar, A. M., & El-Bardini, M. (2014). Practical implementation for the interval type-2 fuzzy PID controller using a low cost microcontroller. Ain Shams Engineering Journal, 5(2), 475-487. |
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66 |
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Mohamed, H., Ahmad, N. B. H., & Shamsuddin, S. M. H. (2014, September). Bijective soft set classification of student's learning styles. In Software Engineering Conference (MySEC), 2014 8th Malaysian (pp. 289-294). IEEE. |
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67 |
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Sharma, B., & Venugopalan, K. (2014). Comparison of neural network training functions for Hematoma classification in brain CT images. Int J Comput Sci Eng, 16(1), 31-35. |
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68 |
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Norlina, M. S., Mazidah, P., Md Sin, N. D., & Rusop, M. (2014, December). Computational intelligence approach in optimization of a nanotechnology process. In Research and Development (SCOReD), 2014 IEEE Student Conference on (pp. 1-5). IEEE. |
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69 |
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Sugimoto Masaya, Igarashi Harukazu, Ishihara Seiji, & Tanaka Ichi-ki (2014) fuzzy control strategy gradient method with the difference between the approach expressed by the rule:. Action decision in RoboCup small size league intelligence and information, 26 (3), 647-657. |
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70 |
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Usman, O. L., & Alaba, O. B. (2014). Predicting Electricity Consumption Using Radial Basis Function (RBF) Network. International Journal of Computer Science and Artificial Intelligence, 4(2), 54. |
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71 |
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George, J. B., Abraham, G. M., Singh, K., Ankolekar, S. M., Amrutur, B., & Sikdar, S. K. (2014). Input coding for neuro-electronic hybrid systems. Biosystems, 126, 1-11. |
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72 |
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Dey, G., & Maringanti, H. B. (2014). Paninian Framework for Odia Language Processing. |
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73 |
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da Costa Martins, J. K. E., Cavalcante, M. S. F. F., de Lima Souza, F. R., & de Araújo, f. m. u. desenvolvimento de um ambiente computacional para ensino de controle fuzzy. |
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74 |
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Piltan, F., Eram, M., Taghavi, M., Sadrnia, O. R., & Jafari, M. (2013). Nonlinear Fuzzy Model-base Technique to Compensate Highly Nonlinear Continuum Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(12), 135. |
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75 |
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Ebrahimi, M. M., Piltan, F., Bazregar, M., & Nabaee, A. (2013). Artificial Chattering Free on-line Modified Sliding Mode Algorithm: Applied in Continuum Robot Manipulator. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(5), 57. |
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76 |
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Mirshekaran, M., Piltan, F., Esmaeili, Z., Khajeaian, T., & Kazeminasab, M. (2013). Design Sliding Mode Modified Fuzzy Linear Controller with Application to Flexible Robot Manipulator. International Journal of Modern Education and Computer Science (IJMECS), 5(10), 53. |
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77 |
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Jahed, A., Piltan, F., Rezaie, H., & Boroomand, B. (2013). Design Computed Torque Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Information Engineering & Electronic Business, 5(3). |
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78 |
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Piltan, F., Mansoorzadeh, M., Zare, S., Shahryarzadeh, F., & Akbari, M. (2013). Artificial tune of fuel ratio: Design a novel siso fuzzy backstepping adaptive variable structure control. International Journal of Electrical and Computer Engineering (IJECE), 3(2), 171-185. |
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79 |
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Piltan, F., Yarmahmoudi, M., Mirzaie, M., Emamzadeh, S., & Hivand, Z. (2013). Design Novel Fuzzy Robust Feedback Linearization Control with Application to Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(5), 1. |
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80 |
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Piltan, F., Nabaee, A., Ebrahimi, M., & Bazregar, M. (2013). Design robust fuzzy sliding mode control technique for robot manipulator systems with modeling uncertainties. International Journal of Information Technology and Computer Science (IJITCS), 5(8), 123. |
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81 |
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Salehi, A., Piltan, F., Mousavi, M., Khajeh, A., & Rashidian, M. R. (2013). Intelligent Robust Feed-forward Fuzzy Feedback Linearization Estimation of PID Control with Application to Continuum Robot. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(1), 1. |
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82 |
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Piltan, F., Bazregar, M., Akbari, M., & Piran, M. (2013). Adjust the fuel ratio by high impact chattering free sliding methodology with application to automotive engine. International Journal of Hybrid Information Technology, 6(1), 13-24. |
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83 |
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Piltan, F., Emamzadeh, S., Heidari, S., Zahmatkesh, S., & Heidari, K. (2013). Design Artificial Intelligent Parallel Feedback Linearization of PID Control with Application to Continuum Robot. International Journal of Engineering and Manufacturing, 3(2), 51-72. |
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84 |
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Piltan, F., Hosainpour, A., Emamzadeh, S., Nazari, I., & Mirzaie, M. (2013). Design Sliding Mode Controller of with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. IAES International Journal of Robotics and Automation (IJRA), 2(4), 149-162. |
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85 |
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Sadrnia, O. R., Piltan, F., Jafari, M., Eram, M., & Shamsodini, M. (2013). Design PID Estimator Fuzzy plus Backstepping to Control of Uncertain Continuum Robot. International Journal of Hybrid Information Technology, 6(4), 31-48. |
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86 |
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Moosavi, M., Eram, M., Khajeh, A., Mahmoudi, O., & Piltan, F. (2013). Design New Artificial Intelligence Base Modified PID Hybrid Controller for Highly Nonlinear System. International Journal of Advanced Science and Technology, 57. |
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87 |
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Boukens, M., & Boukabou, A. (2013, October). PD with fuzzy compensator control of robot manipulators: Experimental study. In Systems and Control (ICSC), 2013 3rd International Conference on (pp. 973-978). IEEE. |
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88 |
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Piltan, F., Badri, A., Meigolinedjad, J., & Keshavarz, M. (2013). Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(9), 103. |
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89 |
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Piltan, F., Mehrara, S., Meigolinedjad, J., & Bayat, R. (2013). Design Serial Fuzzy Variable Structure Compensator for Linear PD Controller: Applied to Rigid Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(11), 111. |
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90 |
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Bazregar, M., Piltan, F., Akbari, M., & Piran, M. (2013). Management of Automotive Engine Based on Stable Fuzzy Technique with Parallel Sliding Mode Optimization. International Journal of Information Technology and Computer Science (IJITCS), 6(1), 101. |
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91 |
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Piltan, F., Bairami, M. A., Aghayari, F., & Rashidian, M. R. (2013). Stable Fuzzy PD Control with Parallel Sliding Mode Compensation with Application to Rigid Manipulator. International Journal of Information Technology and Computer Science (IJITCS), 5(7), 103. |
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92 |
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Shamsodini, M., Piltan, F., Jafari, M., reza Sadrnia, O., & Mahmoudi, O. (2013). Design Modified Fuzzy Hybrid Technique: Tuning By GDO. International Journal of Modern Education and Computer Science (IJMECS), 5(8), 58. |
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93 |
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Piltan, F., Zare, S., ShahryarZadeh, F., & Mansoorzadeh, M. (2013). Supervised Optimization of Fuel Ratio in IC Engine Based on Design Baseline Computed Fuel Methodology. International Journal of Information Technology and Computer Science (IJITCS), 5(4), 76. |
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94 |
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Piltan, F., Jafari, M., Eram, M., Mahmoudi, O., & Sadrnia, O. R. (2013). Design Artificial Intelligence-Based Switching PD plus Gravity for Highly Nonlinear Second Order System. International Journal of Engineering and Manufacturing (IJEM), 3(1), 38. |
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95 |
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Jalali, A., Piltan, F., Hashemzadeh, H., Hasiri, A., & Hashemzadeh, M. (2013). Design Novel Soft Computing Backstepping Controller with Application to Nonlinear Dynamic Uncertain System. International Journal of Intelligent Systems and Applications (IJISA), 5(10), 93. |
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96 |
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Moosavi, M., Eram, M., Khajeh, A., Mahmoudi, O., & Piltan, F. (2013). Design New Artificial Intelligence Base Modified PID Hybrid Controller for Highly Nonlinear System. International Journal of Advanced Science and Technology, 57. |
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97 |
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Bayat, R. (2013). Artificial Intelligence SVC Based Control of Two Machine Transmission System. International Journal of Intelligent Systems and Applications (IJISA), 5(8), 1. |
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98 |
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Piltan, F., Piran, M., Bazregar, M., & Akbari, M. (2013). Design High Impact Fuzzy Baseline Variable Structure Methodology to Artificial Adjust Fuel Ratio. International Journal of Intelligent Systems and Applications (IJISA), 5(2), 59. |
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99 |
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Khoiy, K. A., Davatgarzadeh, F., Taheri, M., & Damavand, I. A Review on Fuzzy-Logic Method to Control Robotic Manipulator Systems. |
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100 |
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Roper, D. (2013). Energy based control system designs for underactuated robot fish propulsion. |
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101 |
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Jiang, S. Y., & Wang, L. X. (2013). Unsupervised Feature Selection Method for Imbalanced Data. Journal of Chinese Computer Systems, 34(1), 63-67. |
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102 |
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Reyes, J. A., Montes, A., González, J. G., & Pinto, D. E. (2013). Clasificación de roles semánticos usando características sintácticas, semánticas y contextuales. Computación y sistemas, 17(2), 263-272. |
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103 |
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Jiangsheng Yi, & Wanglian Xi. (2013). Unsupervised feature unbalanced data selection method. Small Computer Systems, 34 (1), 63-66. |
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104 |
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Uma, S., Chitra, A., & Suganthi, J. (2013). Design of a non-linear time series prediction model for daily electricity demand forecasting. International Journal of Business Innovation and Research, 7(3), 298-317. |
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105 |
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Mesri, A., Khoei, A., & Hadidi, K. (2013, May). Hardware implementation of interval type-2 fuzzy logic controller. In Electrical Engineering (ICEE), 2013 21st Iranian Conference on (pp. 1-6). IEEE. |
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106 |
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Khosla, M., Sarin, R. K., & Uddin, M. (2012). A simplified architecture for triangular quasi type-2 fuzzy logic systems. International Journal of Computational Intelligence Studies, 1(4), 349-367.Khosla, M., Sarin, R. K., & Uddin, M. (2012, July). Implementation of interval type-2 fuzzy systems with analog modules. In Control and System Graduate Researc |
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107 |
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Singh, V. K., Baghel, A., & Negi, S. K. (2013). Finding New Framework for Resolving Problems in Various Dimensions by the Use of ES: An Efficient and Effective Computer Oriented Artificial Intelligence Approach. Innovative Systems Design and Engineering, 4(11), 1-6. |
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108 |
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Jiangsheng Yi, & Wanglian Xi. (2013). Unsupervised feature selection method for imbalanced data. Computer Systems, 34 (1), 63-67. |
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109 |
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Eboña, K. M. L., Llorca Jr, O. S., Perez, G. P., Roldan, J. M., Domingo, I. V. R., & Sagum, R. A. (2013). Named-Entity Recognizer (NER) for Filipino Novel Excerpts using Maximum Entropy Approach. Journal of Industrial and Intelligent Information Vol, 1(1). |
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110 |
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Jimmy, L., & Kaur, D. (2013). Named entity recognition in Manipuri: a hybrid approach. In Language Processing and Knowledge in the Web (pp. 104-110). Springer Berlin Heidelberg. |
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111 |
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Reyes, J. A., Montes, A., González, J. G., & Pinto, D. E. (2013). Classifying Case Relations using Syntactic, Semantic and Contextual Features. Computación y Sistemas, 17(2). |
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112 |
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Wahyunggoro, O., Permanasari, A. E., & Chamsudin, A. Utilization of Neural Network for Disease Forecasting. |
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113 |
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Ÿö, Ÿ. Proof Version. |
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114 |
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Thilagalakshmi, A. (2013, July). Simulation of Neuro-PID Controller for Pressure Process. In IJCA Proceedings on International Conference on Innovations In Intelligent Instrumentation, Optimization and Electrical Sciences (No. 9, pp. 18-21). Foundation of Computer Science (FCS). |
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115 |
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Shrivastava, A., Baghel, M., & Gupta, H. (2013). A Novel Hybrid Feature Selection and Intrusion Detection Based On PCNN and Support Vector Machine. International Journal of Computer Technology and Applications, 4(6), 922. |
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116 |
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Ivaniuk, D. Neuro-PID Controller for a Pasteurizer. |
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117 |
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Lashari, S. A., & Ibrahim, R. (2013). A Framework for Medical Images Classification Using Soft Set. Procedia Technology, 11, 548-556. |
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118 |
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Piltan, F., Mansoorzadeh, M., Zare, S., Shahryarzadeh, F., & Akbari, M. (2013). Artificial tune of fuel ratio: Design a novel siso fuzzy backstepping adaptive variable structure control. International Journal of Electrical and Computer Engineering (IJECE), 3(2), 171-185. |
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119 |
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Piltan, F., Nabaee, A., Ebrahimi, M., & Bazregar, M. (2013). Design robust fuzzy sliding mode control technique for robot manipulator systems with modeling uncertainties. International Journal of Information Technology and Computer Science (IJITCS), 5(8), 123. |
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120 |
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Al-Milli, N. (2013). Backpropagation Neural Network for Prediction of Heart Disease. Journal of Theoretical and Applied Information Technology, 56(1), 131-135. |
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121 |
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LD, V. A. Simulation of Neuro-PID Controller for Pressure Process. |
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122 |
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Shrivastava, A., Baghel, M., & Gupta, H. (2013). A Review of Intrusion Detection Technique by Soft Computing and Data Mining Approach. International Journal of Advanced Computer Research, 3(3), 224. |
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123 |
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Lake, D. (2013). Web-Based Expert System for Cattle Diseases Diagnose (Doctoral dissertation, Addis Ababa University). |
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124 |
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Jalali, A., Piltan, F., Hashemzadeh, M., BibakVaravi, F., & Hashemzadeh, H. (2013). Design Parallel Linear PD Compensation by Fuzzy Sliding Compensator for Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(12), 97. |
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125 |
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Rubio, E., & Castillo, O. (2013, April). Interval type-2 fuzzy clustering for membership function generation. In Hybrid Intelligent Models and Applications (HIMA), 2013 IEEE Workshop on (pp. 13-18). IEEE. |
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126 |
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Piltan, F., Yarmahmoudi, M., Mirzaie, M., Emamzadeh, S., & Hivand, Z. (2013). Design Novel Fuzzy Robust Feedback Linearization Control with Application to Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(5), 1. |
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127 |
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Jalali, A., Piltan, F., Hashemzadeh, H., Hasiri, A., & Hashemzadeh, M. (2013). Design Novel Soft Computing Backstepping Controller with Application to Nonlinear Dynamic Uncertain System. International Journal of Intelligent Systems and Applications (IJISA), 5(10), 93. |
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128 |
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Sadrnia, O. R., Piltan, F., Jafari, M., Eram, M., & Shamsodini, M. (2013). Design PID Estimator Fuzzy plus Backstepping to Control of Uncertain Continuum Robot. International Journal of Hybrid Information Technology, 6(4), 31-48. |
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129 |
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Piltan, F., Hosainpour, A., Emamzadeh, S., Nazari, I., & Mirzaie, M. (2013). Design Sliding Mode Controller of with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. IAES International Journal of Robotics and Automation (IJRA), 2(4), 149-162. |
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130 |
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Jalali, A., Piltan, F., Hashemzadeh, M., BibakVaravi, F., & Hashemzadeh, H. (2013). Design Parallel Linear PD Compensation by Fuzzy Sliding Compensator for Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(12), 97. |
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131 |
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Piltan, F., Emamzadeh, S., Heidari, S., Zahmatkesh, S., & Heidari, K. (2013). Design Artificial Intelligent Parallel Feedback Linearization of PID Control with Application to Continuum Robot. International Journal of Engineering and Manufacturing, 3(2), 51-72. |
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132 |
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Ebrahimi, M. M., Piltan, F., Bazregar, M., & Nabaee, A. (2013). Artificial Chattering Free on-line Modified Sliding Mode Algorithm: Applied in Continuum Robot Manipulator. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(5), 57. |
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133 |
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Piltan, F., ShahryarZadeh, F., Mansoorzadeh, M., & Zare, S. (2013). Robust Fuzzy PD Method with Parallel Computed Fuel Ratio Estimation Applied to Automotive Engine. International Journal of Intelligent Systems and Applications (IJISA), 5(8), 83. |
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134 |
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Mirshekaran, M., Piltan, F., Esmaeili, Z., Khajeaian, T., & Kazeminasab, M. (2013). Design Sliding Mode Modified Fuzzy Linear Controller with Application to Flexible Robot Manipulator. International Journal of Modern Education and Computer Science (IJMECS), 5(10), 53. |
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135 |
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Jahed, A., Piltan, F., Rezaie, H., & Boroomand, B. (2013). Design Computed Torque Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Information Engineering & Electronic Business, 5(3). |
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136 |
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Piltan, F., Bazregar, M., Akbari, M., & Piran, M. (2013). Adjust the fuel ratio by high impact chattering free sliding methodology with application to automotive engine. International Journal of Hybrid Information Technology, 6(1), 13-24. |
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137 |
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Piltan, F., Eram, M., Taghavi, M., Sadrnia, O. R., & Jafari, M. (2013). Nonlinear Fuzzy Model-base Technique to Compensate Highly Nonlinear Continuum Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(12), 135. |
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138 |
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Piltan, F., Piran, M., Bazregar, M., & Akbari, M. (2013). Design High Impact Fuzzy Baseline Variable Structure Methodology to Artificial Adjust Fuel Ratio. International Journal of Intelligent Systems and Applications (IJISA), 5(2), 59. |
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139 |
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Ebrahimi, M. M., Piltan, F., Bazregar, M., & Nabaee, A. (2013). Intelligent Robust Fuzzy-Parallel Optimization Control of a Continuum Robot Manipulator. International Journal of Control and Automation, 6(3), 15-34. |
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140 |
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Piltan, F., Jafari, M., Eram, M., Mahmoudi, O., & Sadrnia, O. R. (2013). Design Artificial Intelligence-Based Switching PD plus Gravity for Highly Nonlinear Second Order System. International Journal of Engineering and Manufacturing (IJEM), 3(1), 38. |
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141 |
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Piltan, F., Zare, S., ShahryarZadeh, F., & Mansoorzadeh, M. (2013). Supervised Optimization of Fuel Ratio in IC Engine Based on Design Baseline Computed Fuel Methodology. International Journal of Information Technology and Computer Science (IJITCS), 5(4), 76. |
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142 |
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Shamsodini, M., Piltan, F., Jafari, M., reza Sadrnia, O., & Mahmoudi, O. (2013). Design Modified Fuzzy Hybrid Technique: Tuning By GDO. International Journal of Modern Education and Computer Science (IJMECS), 5(8), 58. |
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143 |
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Karlk, B., & Harman, G. (2013, April). Computer-aided software for early diagnosis of eerythemato-squamous diseases. In Electronics and Nanotechnology (ELNANO), 2013 IEEE XXXIII International Scientific Conference (pp. 276-279). IEEE. |
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144 |
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Chattopadhyay, S. (2013). Mining the risk of heart attack: a comprehensive study. International Journal of Biomedical Engineering and Technology, 11(4), 394-410. |
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145 |
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Salehi, A., Piltan, F., Mousavi, M., Khajeh, A., & Rashidian, M. R. (2013). Intelligent Robust Feed-forward Fuzzy Feedback Linearization Estimation of PID Control with Application to Continuum Robot. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(1), 1. |
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146 |
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Piltan, F., Badri, A., Meigolinedjad, J., & Keshavarz, M. (2013). Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(9), 103. |
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147 |
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Piltan, F., Bazregar, M., Akbari, M., & Piran, M. (2013). Management of Automotive Engine Based on Stable Fuzzy Technique with Parallel Sliding Mode Optimization. International Journal of Advances in Applied Sciences, 2(4), 171-184. |
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148 |
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Bazregar, M., Piltan, F., Akbari, M., & Piran, M. (2013). Management of Automotive Engine Based on Stable Fuzzy Technique with Parallel Sliding Mode Optimization. International Journal of Information Technology and Computer Science (IJITCS), 6(1), 101. |
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149 |
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Piltan, F., Bairami, M. A., Aghayari, F., & Rashidian, M. R. (2013). Stable Fuzzy PD Control with Parallel Sliding Mode Compensation with Application to Rigid Manipulator. International Journal of Information Technology and Computer Science (IJITCS), 5(7), 103. |
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150 |
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Piltan, F., Mehrara, S., Meigolinedjad, J., & Bayat, R. (2013). Design Serial Fuzzy Variable Structure Compensator for Linear PD Controller: Applied to Rigid Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(11), 111. |
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151 |
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Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology. |
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152 |
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Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Methodology of Mathematical Error-Based Tuning Sliding Mode Controller. International Journal of Engineering, 6(2), 96-117. |
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153 |
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Piltan, F., Nazari, I., Siamak, S., & Ferdosali, P. (2012). Methodology of FPGA-based mathematical error-based tuning sliding mode controller. International Journal of Control and Automation, 5(1), 89-118. |
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154 |
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Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141. |
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155 |
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Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology. |
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156 |
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Piltan, F., Hosainpour, A., Mazlomian, E., Shamsodini, M., & Yarmahmoudi, M. H. (2012). Online Tuning Chattering Free Sliding Mode Fuzzy Control Design: Lyapunov Approach. International Journal of Robotics and Automation, 3(3), 77-105. |
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157 |
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Piltan, F., Yarmahmoudi, M. H., Shamsodini, M., Mazlomian, E., & Hosainpour, A. (2012). PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate Nonlinear Control and MATLAB Courses. International Journal of Robotics and Automation, (3), 167-191. |
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158 |
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Piltan, F., Hosainpour, A., Mazlomian, E., Shamsodini, M., & Yarmahmoudi, M. H. (2012). Online Tuning Chattering Free Sliding Mode Fuzzy Control Design: Lyapunov Approach. International Journal of Robotics and Automation, 3(3), 77-105. |
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159 |
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Piltan, F., Emamzadeh, S., Hivand, Z., Shahriyari, F., & Mirazaei, M. (2012). PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate/Undergraduate Nonlinear Control, Robotics and MATLAB Courses. International Journal of Robotics and Automation, 3(3), 106-150. |
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160 |
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Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology. International Journal of Intelligent Systems and Applications (IJISA), 4(11), 40. |
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161 |
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Piltan, F., Dialame, M., Zare, A., & Badri, A. (2012). Design Novel Lookup Table Changed Auto Tuning FSMC: Applied to Robot Manipulator. International Journal of Engineering, 6(1), 25-41. |
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162 |
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Piltan, F., Aghayari, F., Rashidian, M. R., & Shamsodini, M. (2012). A New Estimate Sliding Mode Fuzzy Controller for Robotic Manipulator. International Journal of Robotics and Automation, 3(1), 45-58. |
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163 |
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Piltan, F., Meigolinedjad, J., Mehrara, S., & Rahmdel, S. (2012). Evaluation Performance of 2nd Order Nonlinear System: Baseline Control Tunable Gain Sliding Mode Methodology. International Journal of Robotics and Automation, 3(3), 192-211. |
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164 |
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Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology. International Journal of Intelligent Systems and Applications (IJISA), 4(11), 40. |
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165 |
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Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141. |
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166 |
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Piltan, F., Dialame, M., Zare, A., & Badri, A. (2012). Design Novel Lookup Table Changed Auto Tuning FSMC: Applied to Robot Manipulator. International Journal of Engineering, 6(1), 25-41. |
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167 |
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Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Methodology of Mathematical Error-Based Tuning Sliding Mode Controller. International Journal of Engineering, 6(2), 96-117. |
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168 |
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Piltan, F., Nazari, I., Siamak, S., & Ferdosali, P. (2012). Methodology of FPGA-based mathematical error-based tuning sliding mode controller. International Journal of Control and Automation, 5(1), 89-118. |
|
169 |
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Piltan, F., Emamzadeh, S., Hivand, Z., Shahriyari, F., & Mirazaei, M. (2012). PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate/Undergraduate Nonlinear Control, Robotics and MATLAB Courses. International Journal of Robotics and Automation, 3(3), 106-150. |
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170 |
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Piltan, F., Siamak, S., Bairami, M. A., & Nazari, I. (2012). Gradient descent optimal chattering free sliding mode fuzzy control design: LYAPUNOV approach. International Journal of Advanced Science and Technology, 43, 73-90. |
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171 |
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Piltan, F., Piran, M., Akbari, M., & Barzegar, M. (2012). Baseline Tuning Methodology Supervisory Sliding Mode Methodology: Applied to IC Engine. International Journal of Advances in Applied Sciences, 1(3), 116-124. |
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172 |
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Piltan, F., Bayat, R., Mehara, S., & Meigolinedjad, J. (2012). GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace. International Journal of Information Engineering and Electronic Business (IJIEEB), 4(5), 17. |
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173 |
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Piltan, F., & Haghighi, S. T. (2012). Design Gradient Descent Optimal Sliding Mode Control of Continuum Robots. IAES International Journal of Robotics and Automation (IJRA), 1(4), 175-189. |
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174 |
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Piltan, F., Jahed, A., Rezaie, H., & Boroomand, B. (2012). Methodology of Robust Linear On-line High Speed Tuning for Stable Sliding Mode Controller: Applied to Nonlinear System. International Journal of Control and Automation, 5(3), 217-236. |
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175 |
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Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology. |
|
176 |
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Piltan, F., Akbari, M., Piran, M., & Bazregar, M. (2012). Design Model Free Switching Gain Scheduling Baseline Controller with Application to Automotive Engine. International Journal of Information Technology and Computer Science (IJITCS), 5(1), 65. |
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177 |
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Seven Tir Ave, S. Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2 nd Order Nonlinear System. |
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178 |
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Piltan, F., Meigolinedjad, J., Mehrara, S., & Rahmdel, S. (2012). Evaluation Performance of 2nd Order Nonlinear System: Baseline Control Tunable Gain Sliding Mode Methodology. International Journal of Robotics and Automation, 3(3), 192-211. |
|
179 |
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Piltan, F., Aghayari, F., Rashidian, M. R., & Shamsodini, M. (2012). A New Estimate Sliding Mode Fuzzy Controller for Robotic Manipulator. International Journal of Robotics and Automation, 3(1), 45-58. |
|
180 |
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Piltan, F., Jahed, A., Rezaie, H., & Boroomand, B. (2012). Methodology of Robust Linear On-line High Speed Tuning for Stable Sliding Mode Controller: Applied to Nonlinear System. International Journal of Control and Automation, 5(3), 217-236. |
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181 |
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Piltan, F., Akbari, M., Piran, M., & Bazregar, M. (2012). Design Model Free Switching Gain Scheduling Baseline Controller with Application to Automotive Engine. International Journal of Information Technology and Computer Science (IJITCS), 5(1), 65. |
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182 |
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Piltan, F., Bayat, R., Aghayari, F., & Boroomand, B. (2012). Design Error-Based Linear Model-Free Evaluation Performance Computed Torque Controller. International Journal of Robotics and Automation, 3(3), 151-166. |
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183 |
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Seven Tir Ave, S. Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2 nd Order Nonlinear System. |
|
184 |
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Piltan, F., Piran, M., Akbari, M., & Barzegar, M. (2012). Baseline Tuning Methodology Supervisory Sliding Mode Methodology: Applied to IC Engine. International Journal of Advances in Applied Sciences, 1(3), 116-124. |
|
185 |
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Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology. |
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186 |
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Piltan, F., Bayat, R., Mehara, S., & Meigolinedjad, J. (2012). GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace. International Journal of Information Engineering and Electronic Business (IJIEEB), 4(5), 17. |
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187 |
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Piltan, F., Siamak, S., Bairami, M. A., & Nazari, I. (2012). Gradient descent optimal chattering free sliding mode fuzzy control design: LYAPUNOV approach. International Journal of Advanced Science and Technology, 43, 73-90. |
|
188 |
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Piltan, F., Bayat, R., Aghayari, F., & Boroomand, B. (2012). Design Error-Based Linear Model-Free Evaluation Performance Computed Torque Controller. International Journal of Robotics and Automation, 3(3), 151-166. |
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189 |
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Piltan, F., Yarmahmoudi, M. H., Shamsodini, M., Mazlomian, E., & Hosainpour, A. (2012). PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate Nonlinear Control and MATLAB Courses. International Journal of Robotics and Automation, (3), 167-191. |
|
190 |
|
Khosla, M., Sarin, R. K., & Uddin, M. (2012, July). Implementation of interval type-2 fuzzy systems with analog modules. In Control and System Graduate Research Colloquium (ICSGRC), 2012 IEEE (pp. 136-141). IEEE. |
|
191 |
|
Oliveira, M. A. P. D. (2012). High level coordination and decision making of a simulated robotic soccer team. |
|
192 |
|
Jiang accounting only, & Yang (2012) Voice fuzzy feature extraction and codebook training algorithm of Jilin University:. Information Science, 30 (3), 279-284. |
|
193 |
|
Hagras, H., & Wagner, C. (2012). Towards the wide spread use of type-2 fuzzy logic systems in real world applications. Computational Intelligence Magazine, IEEE, 7(3), 14-24. |
|
194 |
|
Asaduzzaman, M., Kabir, A. M. E., Uddin, N., Mollah, A. S., & Nurunnabi, M. A Feature Selection Approach Using Asymmetry. |
|
195 |
|
Chandra, R., & Prihastomo, Y. (2012). Self Driving Car: Artificial Intelligence Approach. Journal TICOM (Technology of Information and Communication), 1(1), 43-48. |
|
196 |
|
Uma, S., & Chitra, A. (2012). Pattern recognition using enhanced non-linear time-series models for predicting dynamic real-time decision making environments. International Journal of Business Information Systems, 11(1), 69-92. |
|
197 |
|
Sathyanarayana, S. A. S. A Hybrid approach for Named Entity Recognition, Classification and Extraction (NERCE) in Kannada Documents. |
|
198 |
|
Swain, D., & Pati, C. Named Entity Disambiguation In Odia. |
|
199 |
|
Abdallah, S., Shaalan, K., & Shoaib, M. (2012). Integrating rule-based system with classification for Arabic named entity recognition. In Computational Linguistics and Intelligent Text Processing (pp. 311-322). Springer Berlin Heidelberg. |
|
200 |
|
Verma, O. P., Singla, R., & Kumar, R. (2012). Intelligent Temperature Controller for Water Bath System. World Academy of Science, Engineering and Technology, International Journal of Computer, Information, Systems and Control Engineering, 6(9). |
|
201 |
|
Piltan, F., & Haghighi, S. T. (2012). Design Gradient Descent Optimal Sliding Mode Control of Continuum Robots. IAES International Journal of Robotics and Automation (IJRA), 1(4), 175-189. |
|
202 |
|
Jahangir, F., Anwar, W., Bajwa, U. I., & Wang, X. (2012, December). N-gram and gazetteer list based named entity recognition for urdu: A scarce resourced language. In Proceedings of the 10th Workshop on Asian Language Resources (pp. 95-104). |
|
203 |
|
Dangare, C. S., & Apte, S. S. (2012). A data mining approach for prediction of heart disease using neural networks. International Journal of Computer Engineering and Technology (IJCET), 3(3). |
|
204 |
|
Prabhu, K., & Bhaskaran, V. M. (2012). Optimization of a control loop using adaptive method. Optimization, 1(3). |
|
205 |
|
Chowdhury, D. R., Majumder, R., Bhattacharjee, D., & Siliguri, S. (2012). Neonatal Disease Diagnosis: AI Based Neuro-Genetic Hybrid Approach. International Journal of Computer Science Issues(IJCSI), 9(5). |
|
206 |
|
Piltan, F., Allahdadi, S., Mohammad, A. B., & Nasiri, H. (2011). Design Auto Adjust Sliding Surface Slope: Applied to Robot Manipulator. International Journal of Robotics and Automation, 3(1), 27-44. |
|
207 |
|
Piltan, F., Bairami, M. A., Aghayari, F., & Allahdadi, S. (2011). Design adaptive artificial inverse dynamic controller: Design sliding mode fuzzy adaptive new inverse dynamic fuzzy controller. International Journal of Robotics and Automation (IJRA), 3(1), 13. |
|
208 |
|
Shoaib, M. (2011). Using Machine Learning to Improve Rule based Arabic Named Entity Recognition. |
|
209 |
|
Igarashi, H., Fukuoka, H., & Ishihara, S. (2011). Policy Gradient Approach for Learning of Soccer Player Agents. In Intelligent Control and Computer Engineering (pp. 137-148). Springer Netherlands. |
|
210 |
|
Seven Tir Ave, S. (2011). Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control. |
|
211 |
|
Dovydaitis, J., Jasinevicius, R., Petrauskas, V., & Vrubliauskas, A. Training, Retraining, and Self-training Procedures for the Fuzzy Logic-Based Intellectualization of IoT&S Environments. International Journal of Fuzzy Systems, 1-11. |
|
212 |
|
Taher, S. A., & Zolfaghari, M. Adaptive Fuzzy Gain-Scheduling Design to Improve Instantaneous Average Current–Sharing Control Scheme for Parallel–Connected Inverters Considering Line Impedance Impact in Microgrid Networks. |
|
213 |
|
Piltan, F., Allahdadi, S., Mohammad, A. B., & Nasiri, H. (2011). Design Auto Adjust Sliding Surface Slope: Applied to Robot Manipulator. International Journal of Robotics and Automation, 3(1), 27-44. |
|
214 |
|
Tan, M. K., Chin, Y. K., Tham, H. J., & Teo, K. T. K. (2011, December). Genetic algorithm based PID optimization in batch process control. In Computer Applications and Industrial Electronics (ICCAIE), 2011 IEEE International Conference on (pp. 162-167). IEEE. |
|
215 |
|
Cuaya, G., Munoz-Meléndez, A., & Morales, E. F. (2011). A minority class feature selection method. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (pp. 417-424). Springer Berlin Heidelberg. |
|
216 |
|
Cesarini, P., Guidera, S., Rana, M. M., Fakrudeen, M., Rana, U., Lewis, M., ... & Tsuji, L. J. (2011). Technological Disintermediation in Design and Higher Education. International Journal of Technology, Knowledge & Society, 7(3). |
|
217 |
|
Piltan, F., Bairami, M. A., Aghayari, F., & Allahdadi, S. (2011). Design adaptive artificial inverse dynamic controller: Design sliding mode fuzzy adaptive new inverse dynamic fuzzy controller. International Journal of Robotics and Automation (IJRA), 3(1), 13. |
|
218 |
|
Seven Tir Ave, S. Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control. |
|
219 |
|
Grando, N., Centeno, T. M., Botelho, S. S. D. C., & Fontoura, F. M. (2010). Forecasting electric energy demand using a predictor model based on liquid state machine. |
|
220 |
|
Almeida, F., Lau, N., & Reis, L. P. (2010). A Survey on Coordination Methodologies for Simulated Robotic Soccer Teams. In MALLOW. |
|
221 |
|
Igarashi, H., Fukuoka, H., & Ishihara, S. (2010). Learning of soccer player agents using a policy gradient method: pass selection. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1). |
|
222 |
|
Igarashi, H., Masaki, J., Suzuki, T., Tonegawa, N., Sano, N., Imaizumi, T., ... & Fukuoka, H. Fifty-Storms: Team Description 2009. |
|
223 |
|
Gurmu, Z. K., & Fan, W. D. (2014). Artificial Neural Network Travel Time Prediction Model for Buses Using Only GPS Data. Journal of Public Transportation, 17(2), 3. |
|
224 |
|
Garg, G., & Sharma, P. (2014). An Analysis of Contrast Enhancement using Activation Functions. International Journal of Hybrid Information Technology, 7(5), 235-244. |
|
225 |
|
Tan, T. G., Teo, J., & Anthony, P. (2014). A comparative investigation of non-linear activation functions in neural controllers for search-based game AI engineering. Artificial Intelligence Review, 41(1), 1-25. |
|
226 |
|
Vukicevic, A. M., Jovicic, G. R., Stojadinovic, M. M., Prelevic, R. I., & Filipovic, N. D. (2014). Evolutionary assembled neural networks for making medical decisions with minimal regret: Application for predicting advanced bladder cancer outcome. Expert Systems with Applications, 41(18), 8092-8100. |
|
227 |
|
KARAN O?uz, BAYRAKTAR Canan, GÜMÜ?KAYA Haluk, KARLIK Bekir, “Diagnosing Diabetes Using Neural Networks on Small Mobile Devices”, Expert Systems with Applications, vol. 39 (2012), pp. 54-60, 2012 |
|
228 |
|
Jaddi, N. S., Abdullah, S., & Hamdan, A. R. (2015). Multi-population cooperative bat algorithm-based optimization of artificial neural network model. Information Sciences, 294, 628-644. |
|
229 |
|
Zhang, C., Jiang, J., Ma, J., Zhang, X., Yang, Q., Ouyang, Q., & Lei, X. (2015). Evaluating soil reinforcement by plant roots using artificial neural networks. Soil Use and Management, 31(3), 408-416. |
|
230 |
|
Feng Chang. (2015) study in depth a positive linear function of neural networks. Computer Engineering and Design, 36 (3), 759-762. |
|
231 |
|
Gautam, C., & Ravi, V. (2015). Data imputation via evolutionary computation, clustering and a neural network. Neurocomputing, 156, 134-142. |
|
232 |
|
Akar, M., Hekim, M., & Orhan, U. (2015). Mechanical fault detection in permanent magnet synchronous motors using equal width discretization-based probability distribution and a neural network model. Turkish Journal of Electrical Engineering & Computer Sciences, 23(3). |
|
233 |
|
Yakovyna Vitaliy, S. (2015). of article. |
|
234 |
|
Deo, R. C., & Sahin, M. (2015). Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia. Atmospheric Research, 161, 65-81. |
|
235 |
|
Rotich, N. (2014). Forecasting of wind speeds and directions with artificial neural networks. |
|
236 |
|
Al Doori, M., & Beyrouti, B. (2014). Credit scoring model based on back propagation neural network using various activation and error function. IJCSNS International Journal of Computer Science and Network Security, 14(3), 16-24. |
|
237 |
|
Sun, W., Su, F., & Wang, L. (2014, December). Improving deep neural networks with multilayer maxout networks. In Visual Communications and Image Processing Conference, 2014 IEEE (pp. 334-337). IEEE. |
|
238 |
|
Dogman, A., & Saatchi, R. (2014). Multimedia traffic quality of service management using statistical and artificial intelligence techniques. IET Circuits, Devices & Systems, 8(5), 367-377. |
|
239 |
|
Kumar, R., Chand, K., & Lal, S. P. (2014). Gene Reduction for Cancer Classification Using Cascaded Neural Network with Gene Masking. In Advances in Artificial Intelligence (pp. 301-306). Springer International Publishing. |
|
240 |
|
Singh, V., & Lai, S. P. (2014, November). Digit recognition using single layer neural network with principal component analysis. In Computer Science and Engineering (APWC on CSE), 2014 Asia-Pacific World Congress on (pp. 1-7). IEEE. |
|
241 |
|
Essai, M. H., & Abd Ellah, A. R. (2014, December). M-Estimators based activation functions for robust neural network learning. In Computer Engineering Conference (ICENCO), 2014 10th International (pp. 70-75). IEEE. |
|
242 |
|
Nedic, V., Despotovic, D., Cvetanovic, S., Despotovic, M., & Babic, S. (2014). Comparison of classical statistical methods and artificial neural network in traffic noise prediction. Environmental Impact Assessment Review, 49, 24-30. |
|
243 |
|
Vijean, V., Hariharan, M., Yaacob, S., & Sulaiman, M. N. B. (2014). Application of clustering techniques for visually evoked potentials based detection of vision impairments. Biocybernetics and Biomedical Engineering, 34(3), 169-177. |
|
244 |
|
Valarmathi, P., & Robinson, S. (2014, December). Efficacy of feature selection techniques for Multilayer Perceptron Neural Network to classify mammogram. In Advanced Computing (ICoAC), 2014 Sixth International Conference on (pp. 26-31). IEEE. |
|
245 |
|
Golovko, A. (2014). Foreign exchange rate movement prediction using triangle chart patterns and artificial neural networks (Doctoral dissertation, Tartu Ülikool). |
|
246 |
|
Amirov, A., Gerget, O., Devjatyh, D., & Gazaliev, A. (2014). Medical Data Processing System Based on Neural Network and Genetic Algorithm. Procedia-Social and Behavioral Sciences, 131, 149-155. |
|
247 |
|
García de Soto, B., Adey, B. T., & Fernando, D. (2014). A Process for the Development and Evaluation of Preliminary Construction Material Quantity Estimation Models Using Backward Elimination Regression and Neural Networks. Journal of Cost Analysis and Parametrics, 7(3), 180-218. |
|
248 |
|
Ramkishore, S., Madhumitha, P., & Palanichamy, P. (2014, September). Comparison of Logistic Regression and Support Vector Machine for the Classification of Microstructure and Interfacial Defects in Zircaloy-2. In Soft Computing and Machine Intelligence (ISCMI), 2014 International Conference on (pp. 130-134). IEEE. |
|
249 |
|
Laqrichi, S., Marmier, F., & Gourc, D. (2014). Software Cost and Duration Estimation Based on Distributed Project Data: A General Framework. In Enterprise Interoperability VI (pp. 213-224). Springer International Publishing. |
|
250 |
|
Genç, B. (2015). A methodology for evaluating utilisation of mine planning software and consequent decision-making strategies in South Africa (Doctoral dissertation, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg). |
|
251 |
|
Laqrichi, S., Marmier, F., Gourc, D., & Nevoux, J. (2015). Integrating uncertainty in software effort estimation using Bootstrap based Neural Networks. IFAC-PapersOnLine, 48(3), 954-959. |
|
252 |
|
Arai, K. Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field. |
|
253 |
|
Sarac, B., Karlik, B., Uncu, U., & Ayhan, T. (2015). Neural Network Methodology for Modeling Heat Transfer in Wake Flow. Journal of Heat Transfer, 137(2), 022201. |
|
254 |
|
Díaz, R., & Hurtado, N. (2012). Uso del Sistema Neuro-Difuso (SND) en Datos de Porosidad y Saturación de Agua, para la Inferencia de Permeabilidad. |
|
255 |
|
Awan, J. A., & Bae, D. H. (2016). Drought prediction over the East Asian monsoon region using the adaptive neuro-fuzzy inference system and the global sea surface temperature anomalies. International Journal of Climatology. |
|
256 |
|
Zainuri, M. A. A. M., Radzi, M. A. M., Soh, A. C., Mariun, N., & Rahim, N. A. (2015). DC-link capacitor voltage control for single-phase shunt active power filter with step size error cancellation in self-charging algorithm. IET Power Electronics. |
|
257 |
|
Gupta, S., & Kashyap, S. (2015). Forecasting inflation in G-7 countries: an application of artificial neural network. foresight, 17(1), 63-73. |
|
258 |
|
Kudlácek, J. (2015). Analýza velkých dat v mobilních sítích. |
|
259 |
|
Wang, A., An, N., Chen, G., Li, L., & Alterovitz, G. (2015). Predicting hypertension without measurement: A non-invasive, questionnaire-based approach. Expert Systems with Applications, 42(21), 7601-7609. |
|
260 |
|
Liu, P. H. (2015). Novel Convolutional Neural Networks for Deep Learning and Its Applications to General Image Classification. |
|
261 |
|
Zissis, D., Xidias, E. K., & Lekkas, D. (2015). Real-time vessel behavior prediction. Evolving Systems, 1-12. |
|
262 |
|
Lu, J., Xue, S., Zhang, X., & Han, Y. (2015). A Neural Network-Based Interval Pattern Matcher. Information, 6(3), 388-398. |
|
263 |
|
Zaki, M., Hamouda, A., & Hisham, B. (2015). Travel Time Prediction under Egypt Heterogeneous Traffic Conditions using Neural Network and Data Fusion. Egyptian Computer Science Journal, 39(2). |
|
264 |
|
Arai, K. Method for Tealeaves Quality Estimation Through Measurements of Degree of Polarization, Leaf Area Index, Photosynthesis Available Radiance and Normalized Difference Vegetation Index for Characterization of Tealeaves. |
|
265 |
|
Arai, K., Sakashita, M., Shigetomi, O., & Miura, Y. Estimation of Protein Content in Rice Crop and Nitrogen Content in Rice Leaves Through Regression Analysis with NDVI Derived from Camera Mounted Radio-Control Helicopter. |
|
266 |
|
Zissis, D., Xidias, E. K., & Lekkas, D. (2015). A cloud based architecture capable of perceiving and predicting multiple vessel behaviour. Applied Soft Computing, 35, 652-661. |
|
267 |
|
Kashyap, Y., Bansal, A., & Sao, A. K. (2015). Spatial Approach of Artificial Neural Network for Solar Radiation Forecasting: Modeling Issues. Journal of Solar Energy, 2015. |
|
268 |
|
Yakovyna, v. s. (2015). software failures prediction using rbf neural network. |
|
269 |
|
Hussain, F., & Jeong, J. (2015, March). Exploiting deep neural networks for digital image compression. In Web Applications and Networking (WSWAN), 2015 2nd World Symposium on (pp. 1-6). IEEE. |
|
270 |
|
Arai, K. Discrimination Method between Prolate and Oblate Shapes of Leaves Based on Polarization Characteristics Measured with Polarization Film Attached Cameras. |
|
271 |
|
Foster, R. (2015). A comparison of machine learning techniques for hand shape recognition. |
|
272 |
|
Jaddi, N. S., Abdullah, S., & Hamdan, A. R. (2015). Optimization of neural network model using modified bat-inspired algorithm. Applied Soft Computing, 37, 71-86. |
|
273 |
|
Wróbel, J., & Kulawik, A. (2015, March). Using the artificial neural networks in the modelling of the induction heating. In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014) (Vol. 1648, p. 850090). AIP Publishing. |
|
274 |
|
Borrotti, M., Pievatolo, A., Critelli, I., Degiorgi, A., & Colledani, M. (2015). A computer-aided methodology for the optimization of electrostatic separation processes in recycling. Applied Stochastic Models in Business and Industry. |
|
275 |
|
Abdi, B., Mozafari, H., Abdullah, M. R., & Ayob, A. (2013). Multi-objective Design of Fibre Metal Laminates for Maximum Impact Resistance using Imperialist Competitive Algorithm and Genetic Algorithm. Global Journal on Technology, 3. |
|
276 |
|
Arai, K., Sasaki, Y., Kasuya, S., & Matusura, H. (2015). Appropriate Tealeaf Harvest Timing Determination Based on NIR Images. |
|
277 |
|
Li, N., Zhang, M., Nie, D., & Jiang, W. Q. (2014). An Analysis of Near-field Scattering Characteristics of Rough Target: From the Perspective of Bidirectional Reflectance Distribution Function Based on LS-SVM. Progress In Electromagnetics Research M, 39, 1-9. |
|
278 |
|
Kashyap, Y., Bansal, A., & Sao, A. K. (2015). Solar radiation forecasting with multiple parameters neural networks. Renewable and Sustainable Energy Reviews, 49, 825-835. |
|
279 |
|
Salem, D. A., Seoud, R. A. A., Kadah, Y. M., & Kadah, Y. M. Robust Classification of MHC Class II Peptides. |
|
280 |
|
Bouzeria, H., Fetha, C., Bahi, T., Abadlia, I., Layate, Z., & Lekhchine, S. (2015). Fuzzy Logic Space Vector Direct Torque Control of PMSM for Photovoltaic Water Pumping System. Energy Procedia, 74, 760-771. |
|
281 |
|
Abdul-Jabbar, D. J., Al-Faydi, S. N. M., & Yahya, H. N. (2015). Neuro-Fuzzy Based ECG Signal Classification with A Gaussian Derivative Filter. Al-Rafadain Engineering Journal, 23(2). |
|
282 |
|
Onieva, E., Hernandez-Jayo, U., Osaba, E., Perallos, A., & Zhang, X. (2015). A Multi-Objective Evolutionary Algorithm for the Tuning of Fuzzy Rule Bases for Uncoordinated Intersections in Autonomous Driving. Information Sciences. |
|
283 |
|
Klimashevich AV Nikolsky, VI, & Bogonina, OV experience in prevention and treatment of post-burn scarring esophageal strictures by stenting. (Repeat after neg reviews). HERALD Surgical Gastroenterology, 68. |
|
284 |
|
Murugadoss, R., & Ramakrishnan, M. Nonlinear Approximations in Sigmoid Transfer Function for Improved Statistical Pattern Recognition Based On PNN Bayesian Approach. |
|
285 |
|
Murugadoss, R., & Ramakrishnan, M. universal approximation with non-sigmoid hidden layer activation functions by using artificial neural network modeling. |
|
286 |
|
Mondal, K. Recognition of Static Hand Gestures of Alphabet in Bangla Sign Language. |
|
287 |
|
Tantawy, M., & Zorkany, M. A Suitable Approach for Evaluating Bus Arrival Time Prediction Techniques in Egypt. algorithms, 2, 9. |
|
288 |
|
Cazella, S. C. Thiago Nunes Kehl Viviane Todt Maurício Roberto Veronez. |
|
289 |
|
Sakthivel, S., & Habeeb, S. K. M. NNvPDB: Neural Network based Protein Secondary Structure Prediction with PDB Validation. |
|
290 |
|
Karlik, B., Uncu, U., & Ayhan, T. Neural Network Methodology for Modeling Heat Transfer in Wake Flow. |
|
291 |
|
Grd, P. two-dimensional face image classification for distinguishing children from adults based on anthropometry. |
|
292 |
|
Tosatto, S. C. Neural-Symbolic Learning: How to play Soccer. In Seventh International Workshop on Neural-Symbolic Learning and Reasoning (p. 36). |
|
293 |
|
Klimashevich, A. Nikolsky, VM, BOGONINA, O., & KUVAKOVA, R. (2012). Neural network model in treating and preventing post-burn scar formation of structures esophagus. fundamental research (2-0). |
|
294 |
|
Supriyono, H., & Tokhi, M. O. (2012, February). Dynamic Neuro-modelling Using Bacterial Foraging Optimisation with Fuzzy Adaptation. In Intelligent Systems, Modelling and Simulation (ISMS), 2012 Third International Conference on (pp. 109-114). IEEE. |
|
295 |
|
Al-zahra, K. A., Moosa, K., & Jasim, B. H. (2015). A comparative Study of Forecasting the Electrical Demand in Basra city using Box-Jenkins and Modern Intelligent Techniques. Iraqi Journal for Electrical & Electronic Engineering, 11(1). |
|
296 |
|
Al-Enzi, J., Al-Sharhan, S., & Abbod, M. (2014). A new intelligent artificial immune systems based ensemble for high-dimensional data clustering. International Journal of Hybrid Intelligent Systems, 11(3), 167-181. |
|
297 |
|
Singh, P., & Arora, S. Adaptive Perturb and Observe-Fuzzy Control Maximum Power Point Tracking for Photovoltaic Boost DC-DC Converter. |
|
298 |
|
Iatan, I. F. (2012). A Concurrent Fuzzy Neural Network Approach for a Fuzzy Gaussian Neural Network. Blucher Mechanical Engineering Proceedings, 1(1), 3018-3025. |
|
299 |
|
Garrido, A. (2012). Axiomatic of Fuzzy Complex Numbers. Axioms, 1(1), 21-32. |
|
300 |
|
Al-Enezi, J. (2012). Artificial immune systems based committee machine for classification application (Doctoral dissertation, Brunel University). |
|
301 |
|
Mohd Zainuri, M., Radzi, M., Amran, M., Soh, A. C., & Rahim, N. A. (2012, December). Adaptive P&O-fuzzy control MPPT for PV boost dc-dc converter. In Power and Energy (PECon), 2012 IEEE International Conference on (pp. 524-529). IEEE. |
|
302 |
|
Mirinejad, H., Welch, K. C., & Spicer, L. (2012, May). A review of intelligent control techniques in HVAC systems. In Energytech, 2012 IEEE (pp. 1-5). IEEE. |
|
303 |
|
Aji, S., Ajiatmo, D., Robandi, I., & Suryoatmojo, H. (2013). MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car. Journal of Mechatronics, Electrical Power, and Vehicular Technology, 4(2), 127-134. |
|
304 |
|
De Canete, J. F., Garcia-Cerezo, A., García-Moral, I., Del Saz, P., & Ochoa, E. (2013). Object-oriented approach applied to ANFIS modeling and control of a distillation column. Expert Systems with Applications, 40(14), 5648-5660. |
|
305 |
|
Yuste, A. J., Triviño, A., & Casilari, E. (2013). Type-2 fuzzy decision support system to optimise MANET integration into infrastructure-based wireless systems. Expert Systems with Applications, 40(7), 2552-2567. |
|
306 |
|
Kar, S., Das, S., & Ghosh, P. K. (2014). Applications of neuro fuzzy systems: A brief review and future outline. Applied Soft Computing, 15, 243-259. |
|
307 |
|
Ravizza, S., Chen, J., Atkin, J. A., Stewart, P., & Burke, E. K. (2014). Aircraft taxi time prediction: Comparisons and insights. Applied Soft Computing, 14, 397-406. |
|
308 |
|
Mohd Zainuri, M., Radzi, M., Amran, M., Soh, A. C., & Rahim, N. A. (2014). Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc-dc converter. Renewable Power Generation, IET, 8(2), 183-194. |
|
309 |
|
Bouzeria, H., Fetha, C., Bahi, T., Lekhchine, S., & Rachedi, L. (2014). Speed Control of Photovoltaic Pumping System. International Journal of Renewable Energy Research (IJRER), 4(3), 705-713. |
|
310 |
|
Bouzeria, H., Fetha, C., Bahi, T., Lekhchine, S., & Layate, Z. (2014, October). Fuzzy logic of speed control for photovoltaic pumping system. In Renewable and Sustainable Energy Conference (IRSEC), 2014 International (pp. 136-140). IEEE. |
|
311 |
|
Awan, J. A., & Bae, D. H. (2014). Improving ANFIS based model for long-term dam inflow prediction by incorporating monthly rainfall forecasts. Water resources management, 28(5), 1185-1199. |
|
312 |
|
Soares, F. A. A. D. M. (2012). Predição recursiva de diâmetros de clones de eucalipto utilizando rede Perceptron de múltiplas camadas para o cálculo de volume (Doctoral dissertation). |
|
313 |
|
Tasic, J. (2012). Procesiranje slikovnih analogija neuronskim mrežama. |
|
314 |
|
Mohamad, M., Saman, M. Y. M., & Hitam, M. S. (2012, October). A framework for multiprocessor neural networks systems. In ICT Convergence (ICTC), 2012 International Conference on (pp. 44-48). IEEE. |
|
315 |
|
Vijean, V., Hariharan, M., Yaacob, S., Sulaiman, M. N. B., & Adom, A. H. (2013). Objective investigation of vision impairments using single trial pattern reversal visually evoked potentials. Computers & Electrical Engineering, 39(5), 1549-1560. |
|
316 |
|
Aziz, N. A., Abdullah, W. F. H., Md Tahir, N., Adenan, M. N. H., & Jamil, W. (2013, August). Enhancement of CHEMFET sensor selectivity based on backpropagation algorithm. In System Engineering and Technology (ICSET), 2013 IEEE 3rd International Conference on (pp. 226-231). IEEE. |
|
317 |
|
Zaki, M., Ashour, I., Zorkany, M., & Hesham, B. (2013). Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman filter Techniques. International Journal of Modern Engineering Research, 3(4), 2035-2041. |
|
318 |
|
Yerrabolu, P., Mareddy, L., Bhatt, D., Aggarwal, P., Kumar, A., & Devabhaktuni, V. (2013). Correction Model-Based ANN Modeling Approach for the Estimation of Radon Concentrations in Ohio. Environmental Progress & Sustainable Energy, 32(4), 1223-1233. |
|
319 |
|
Devabhaktuni, V., Bunting, C. F., Green, D., Kvale, D., Mareddy, L., & Rajamani, V. (2013). A new ANN-based modeling approach for rapid EMI/EMC analysis of PCB and shielding enclosures. Electromagnetic Compatibility, IEEE Transactions on, 55(2), 385-394. |
|
320 |
|
Horng, S. C., & Lin, S. Y. (2013). Evolutionary algorithm assisted by surrogate model in the framework of ordinal optimization and optimal computing budget allocation. Information Sciences, 233, 214-229. |
|
321 |
|
AlBakkar, A. (2014). Adaptive Simplified Neuro-Fuzzy Controller as Supplementary Stabilizer for SVC. |
|
322 |
|
Rotich, N. K., Backman, J., Linnanen, L., & Daniil, P. (2014). Wind Resource Assessment and Forecast Planning with Neural Networks. Journal of Sustainable Development of Energy, Water and Environment Systems, 2(2), 174-190. |
|
323 |
|
Jeong, K. (2014). Learning from e-learning: Testing Intelligent Learning Systems in South Asia. |
|
324 |
|
Viswanathan, a., & chitra, s. (2014). optimized radial basis function classifier with hybrid bat algorithm for multi modal biometrics. journal of theoretical & applied information technology, 67(1). |
|
325 |
|
Mohan, A. (2014). A New Spatio-Temporal Data Mining Method and its Application to Reservoir System Operation (Doctoral dissertation, University of Nebraska). |
|
326 |
|
ULER, H. G., Sahin, M., & Ferikoglu, A. (2014). Feature selection on single-lead ECG for obstructive sleep apnea diagnosis. Turkish Journal of Electrical Engineering & Computer Sciences, 22, 465-478. |
|
327 |
|
Zhou, Q., & Li, Z. (2014). Use of Artificial Neural Networks for Selective Omission in Updating Road Networks. The Cartographic Journal, 51(1), 38-51. |
|
328 |
|
Al-Khasawneh, A., & Hijazi, H. (2014). A Predictive E-Health Information System: Diagnosing Diabetes Mellitus Using Neural Network Based Decision Support System. International Journal of Decision Support System Technology (IJDSST), 6(4), 31-48. |
|
329 |
|
Arvidsson, J. (2014). Forecasting on-demand video viewership ratingsusing neural networks. |
|
330 |
|
KARLIK, B. (2013). Soft Computing Methods in Bioinformatics: A Comprehensive Review. Mathematical and Computational Applications, 18(3), 176-197. |
|
331 |
|
Yeremia, H., Yuwono, N. A., Raymond, P., & Budiharto, W. (2013). Genetic algorithm and neural network for optical character recognition. Journal of Computer Science, 9(11), 1435. |
|
332 |
|
Hilbish, N. (2012). Multiple Fundamental Frequency Pitch Detection for Real Time MIDI Applications. |
|
333 |
|
Isa, I. S., Fauzi, N. A., Sharif, J. M., Baharudin, R., & Abbas, M. H. (2012, November). Comparisons of MLP transfer functions for different classification classes. In Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on (pp. 110-114). IEEE. |
|
334 |
|
Zhou, Q. (2012). Selective omission of road networks in multi-scale representation (Doctoral dissertation, The Hong Kong Polytechnic University). |
|
335 |
|
Supriyono, H. (2012). Novel bacterial foraging optimisation algorithms with application to modelling and control of flexible manipulator systems. |
|
336 |
|
Anjo, M. D. S., Pizzolato, E. B., & Feuerstack, S. (2012, November). A real-time system to recognize static gestures of Brazilian sign language (libras) alphabet using Kinect. In Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems (pp. 259-268). Brazilian Computer Society. |
|
337 |
|
Karan, O., Bayraktar, C., Gümüskaya, H., & Karlik, B. (2012). Diagnosing diabetes using neural networks on small mobile devices. Expert Systems with Applications, 39(1), 54-60. |
|
338 |
|
Yücelbas, S. (2013). Hibrit siniflayicilar kullanarak kalpteki ritim bozukluklarinin teshisi (Doctoral dissertation, Selçuk Üniversitesi Fen Bilimleri Enstitüsü). |
|
339 |
|
Fera, M., Lambiase, A., Fruggiero, F., Martino, G., & Nenni, M. E. (2013). Production Scheduling Approaches for Operations Management. INTECH Open Access Publisher. |
|
340 |
|
Parvin, A. (2013). Application of Neural Networks with CSD Coefficients for Human Face Recognition. |
|
341 |
|
Vijean, V., Hariharan, M., Yaacob, S., & Sulaiman, M. N. B. (2013). Stockwell transform and clustering techniques for efficient detection of vision impairments from single trial VEPs. International Journal of Medical Engineering and Informatics, 5(4), 352-371. |
|
342 |
|
Klimashevich AV Nikolsky, VI, Bogonina, OV, Akimov, AA, & Shabrov, AV (2013). A method of predicting esophageal stricture scar AFTER burns. Fundamental research (2-1). |
|
343 |
|
Velican, v. (2013). teza de doctorat (doctoral dissertation, academia tehnica militara). |
|
344 |
|
Saputri, T. R. D., & Lee, S. W. (2013). Using Artificial Neural Networks for Predicting Traffic Conditions: A Learning Algorithm for Long-term Time Series Forecasting. Journal of Convergence Information Technology, 8(14), 121. |
|
345 |
|
Abd Aziz, N., Latif, A., Al Kasyaf, M., Abdullah, W. F. H., Md Tahir, N., & Zolkapli, M. (2013, November). Hardware implementation of backpropagation algorithm based on CHEMFET sensor selectivity. In Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on (pp. 387-390). IEEE. |
|
346 |
|
Tang, W. (2013). Modeling, Estimation, and Control of Nonlinear Time-Variant Complex Processes (Doctoral dissertation, Texas Tech University). |
|
347 |
|
Asgari, H. (2014). Modelling, Simulation and Control of Gas Turbines Using Artificial Neural Networks. |
|
|
|