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International Journal of Artificial Intelligence and Expert Systems (IJAE)
An International peer-review journal operated under CSC-OpenAccess Policy.
ISSN - 2180-124X
Published - Bi-Monthly   |   Established - 2010   |   Year of Publication - 2022

SUBMISSION
June 30, 2022

NOTIFICATION
July 31, 2022

PUBLICATION
August 31, 2022

 
         
HOME   About IJAE   Editorial Board   Call For Papers/Editors   Submission Guidelines   Citation Report   Issues Archive   Subscribe IJAE
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SEE COMPLETE LIST OF PUBLICATIONS
 

IJAE CITATION IMPACT
5.179

Refer to In-Process Citation Report for IJAE for complete details.
 
LIST OF JOURNALS
Complete list of Open Access journals with free access its publications.
 
For Inquiries & Fast Response cscpress@cscjournals.org

CITATION REPORT FOR IJAE

Below calculations are based on citations that are extracted through Google Scholar until December 31, 2020.


Total Citations = 347
Self Citations = 0
Total Publications = 67


Citation Impact
(Total Citations - Self Citations) / Total Publications

Citation Impact
(347 - 0) / 67 = 5.179

 
SR
M-CODE
CITATION
1
Karlik, B. The Positive Effects of Fuzzy C-Means Clustering on Supervised Learning Classifiers.
2
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.
3
Turabieh, H. (2016). A Hybrid ANN-GWO Algorithm for Prediction of Heart Disease. American Journal of Operations Research, 6(02), 136.
4
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.
5
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.
6
Pant, H., & Srivastava, R. MINDEX_IB: A Feature Selection method for Imbalanced Dataset. IONOSPHERE, 34(2), 126-225.
7
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).
8
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.
9
Amarappa, S., & Sathyanarayana, S. V. kannada named entity recognition and classification (nerc) based on multinomial naïve bayes (mnb) classifier.
10
ORESKI, D., & KLICEK, B. A novel feature selection techniques based on contrast set mining.
11
Pant, H., & Srivastava, R. a survey on feature selection methods for imbalanced datasets.
12
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).
13
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.
14
Helwan, A. (2015). Heart Attack Prediction System Based Neural Arbitration. Turkish Online Journal of Science & Technology, 5(2).
15
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).
16
Radhimeenakshi, S., & Nasira, G. M. Prediction of Heart Disease using Neural Network with Back Propagation.
17
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.
18
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.
19
Ross, O. H. M., & Cruz, R. S. (2015). Evolving Embedded Fuzzy Controllers. In Springer Handbook of Computational Intelligence (pp. 1451-1477). Springer Berlin Heidelberg.
20
Akbarzadeh-T, M. R., & Bashari, M. RLS Based Adaptive IVT2 Fuzzy Controller for Uncertain Model of Inverted Pendulum.
21
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.
22
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.
23
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.
24
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.
25
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.
26
Wei, the staff super, & SOCIALIST. (2015). Applied Research in nonlinear control arm of linear quadratic regulator. Journal of Mechanical & Electrical Engineering, 32 (6).
27
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.
28
Freiberg, M. Knowledge-Based-System Usability.
29
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.
30
Han, Z. (2015). Truckload Carrier Selection, Routing and Cost Optimization.
31
Johar, F., Potts, C., & Bennell, J. (2015). Vehicle Routing Problem with Time Constraints. Malaysian Journal of Fundamental and Applied Sciences, 11(4).
32
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.
33
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.
34
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.
35
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.
36
Chitra, D., & Nasira, G. M. (2015). wrapper based feature selection for ct image. ictact journal on image & video processing, 6(1).
37
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.
38
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).
39
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.
40
Abdullah, N., Tiew, Y. W., & Rosmalina, A. R. Export price of sabah sawn timber: now and future? a mathematical approach using neural network.
41
Prerana, P. S. (2015). Comparative Study of GD, LM and SCG Method of Neural Network for Thyroid Disease Diagnosis. IJAR, 1(10), 34-39.
42
Rosmalina, A. R. Forecasting export price of sabah sawn timber using neural network.
43
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).
44
Srikanth, K., & Arivazhagan, D. Prediction Model to Enhance Resource Efficiently For Hospitals.
45
Dey, G., & Maringanti, H. B. (2014). Paninian Framework for Odia Language Processing.
46
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.
47
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.
48
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.
49
Leskelä, C. L. H. (2014). Learning for RoboCup Soccer.
50
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.
51
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.
52
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.
53
Krenek, J., & Kuca, K. Artificial Neural Data M.
54
Ðordevic, m. z. klasifikacija srcanih oboljenja pomocu neuronskih mreta classification of heart diseases using neural networks.
55
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.
56
Latifi, Z., & Karimi, A. (2014). A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot. Procedia Computer Science, 42, 301-307.
57
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.
58
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.
59
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.
60
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.
61
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.
62
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.
63
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.
64
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.
65
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.
66
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.
67
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.
68
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.
69
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.
70
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.
71
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.
72
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.
73
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.
74
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.
75
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).
76
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.
77
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.
78
Jiangsheng Yi, & Wanglian Xi. (2013). Unsupervised feature unbalanced data selection method. Small Computer Systems, 34 (1), 63-66.
79
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.
80
Jiang, S. Y., & Wang, L. X. (2013). Unsupervised Feature Selection Method for Imbalanced Data. Journal of Chinese Computer Systems, 34(1), 63-67.
81
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).
82
Chattopadhyay, S. (2013). Mining the risk of heart attack: a comprehensive study. International Journal of Biomedical Engineering and Technology, 11(4), 394-410.
83
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.
84
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.
85
Roper, D. (2013). Energy based control system designs for underactuated robot fish propulsion.
86
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).
87
Ivaniuk, D. Neuro-PID Controller for a Pasteurizer.
88
Al-Milli, N. (2013). Backpropagation Neural Network for Prediction of Heart Disease. Journal of Theoretical and Applied Information Technology, 56(1), 131-135.
89
Ÿö, Ÿ. Proof Version.
90
Wahyunggoro, O., Permanasari, A. E., & Chamsudin, A. Utilization of Neural Network for Disease Forecasting.
91
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.
92
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
93
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.
94
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.
95
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.
96
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.
97
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.
98
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.
99
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.
100
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).
101
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.
102
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.
103
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.
104
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.
105
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.
106
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.
107
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.
108
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.
109
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.
110
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.
111
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.
112
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.
113
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.
114
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.
115
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.
116
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.
117
Bayat, R. (2013). Artificial Intelligence SVC Based Control of Two Machine Transmission System. International Journal of Intelligent Systems and Applications (IJISA), 5(8), 1.
118
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.
119
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.
120
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.
121
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.
122
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.
123
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.
124
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.
125
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.
126
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.
127
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).
128
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.
129
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.
130
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.
131
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.
132
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.
133
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.
134
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.
135
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.
136
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.
137
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.
138
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.
139
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.
140
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.
141
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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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.
143
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.
144
Khoiy, K. A., Davatgarzadeh, F., Taheri, M., & Damavand, I. A Review on Fuzzy-Logic Method to Control Robotic Manipulator Systems.
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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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Lashari, S. A., & Ibrahim, R. (2013). A Framework for Medical Images Classification Using Soft Set. Procedia Technology, 11, 548-556.
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LD, V. A. Simulation of Neuro-PID Controller for Pressure Process.
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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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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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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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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.
171
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.
172
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.
173
Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141.
174
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.
175
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.
176
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.
177
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.
178
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.
179
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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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.
181
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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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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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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Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
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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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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.
188
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.
189
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.
190
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.
191
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.
192
Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141.
193
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.
194
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.
195
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.
196
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.
197
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.
198
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.
199
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.
200
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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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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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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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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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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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.
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