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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 - 2024

SUBMISSION
April 30, 2024

NOTIFICATION
May 31, 2024

PUBLICATION
June 30, 2024

    
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
4.957
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 = 70


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

Citation Impact
(347 - 0) / 70 = 4.957
 
SR
M-CODE
CITATION
1
 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.
2
 Turabieh, H. (2016). A Hybrid ANN-GWO Algorithm for Prediction of Heart Disease. American Journal of Operations Research, 6(02), 136.
3
 Karlik, B. The Positive Effects of Fuzzy C-Means Clustering on Supervised Learning Classifiers.
4
 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.
5
 Pant, H., & Srivastava, R. MINDEX_IB: A Feature Selection method for Imbalanced Dataset. IONOSPHERE, 34(2), 126-225.
6
 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).
7
 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.
8
 Chitra, D., & Nasira, G. M. (2015). wrapper based feature selection for ct image. ictact journal on image & video processing, 6(1).
9
 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.
10
 Radhimeenakshi, S., & Nasira, G. M. Prediction of Heart Disease using Neural Network with Back Propagation.
11
 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.
12
 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).
13
 Wei, the staff super, & SOCIALIST. (2015). Applied Research in nonlinear control arm of linear quadratic regulator. Journal of Mechanical & Electrical Engineering, 32 (6).
14
 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.
15
 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.
16
 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.
17
 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.
18
 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.
19
 Helwan, A. (2015). Heart Attack Prediction System Based Neural Arbitration. Turkish Online Journal of Science & Technology, 5(2).
20
 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).
21
 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.
22
 Han, Z. (2015). Truckload Carrier Selection, Routing and Cost Optimization.
23
 Johar, F., Potts, C., & Bennell, J. (2015). Vehicle Routing Problem with Time Constraints. Malaysian Journal of Fundamental and Applied Sciences, 11(4).
24
 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.
25
 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).
26
 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.
27
 Pant, H., & Srivastava, R. a survey on feature selection methods for imbalanced datasets.
28
 Rosmalina, A. R. Forecasting export price of sabah sawn timber using neural network.
29
 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).
30
 Amarappa, S., & Sathyanarayana, S. V. kannada named entity recognition and classification (nerc) based on multinomial naïve bayes (mnb) classifier.
31
 Srikanth, K., & Arivazhagan, D. Prediction Model to Enhance Resource Efficiently For Hospitals.
32
 Akbarzadeh-T, M. R., & Bashari, M. RLS Based Adaptive IVT2 Fuzzy Controller for Uncertain Model of Inverted Pendulum.
33
 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.
34
 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.
35
 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.
36
 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.
37
 Freiberg, M. Knowledge-Based-System Usability.
38
 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.
39
 Prerana, P. S. (2015). Comparative Study of GD, LM and SCG Method of Neural Network for Thyroid Disease Diagnosis. IJAR, 1(10), 34-39.
40
 Ross, O. H. M., & Cruz, R. S. (2015). Evolving Embedded Fuzzy Controllers. In Springer Handbook of Computational Intelligence (pp. 1451-1477). Springer Berlin Heidelberg.
41
 Abdullah, N., Tiew, Y. W., & Rosmalina, A. R. Export price of sabah sawn timber: now and future? a mathematical approach using neural network.
42
 ORESKI, D., & KLICEK, B. A novel feature selection techniques based on contrast set mining.
43
 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.
44
 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.
45
 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.
46
 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.
47
 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.
48
 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.
49
 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.
50
 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.
51
 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.
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
 Leskelä, C. L. H. (2014). Learning for RoboCup Soccer.
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
 Krenek, J., & Kuca, K. Artificial Neural Data M.
57
 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.
58
 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.
59
 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.
60
 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.
61
 Latifi, Z., & Karimi, A. (2014). A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot. Procedia Computer Science, 42, 301-307.
62
 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.
63
 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.
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
 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.
66
 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.
67
 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.
68
 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.
69
 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.
70
 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.
71
 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.
72
 Dey, G., & Maringanti, H. B. (2014). Paninian Framework for Odia Language Processing.
73
 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.
74
 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.
75
 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.
76
 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.
77
 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).
78
 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.
79
 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.
80
 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.
81
 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.
82
 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.
83
 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.
84
 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.
85
 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.
86
 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.
87
 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.
88
 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.
89
 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.
90
 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.
91
 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.
92
 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.
93
 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.
94
 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.
95
 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.
96
 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.
97
 Bayat, R. (2013). Artificial Intelligence SVC Based Control of Two Machine Transmission System. International Journal of Intelligent Systems and Applications (IJISA), 5(8), 1.
98
 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.
99
 Khoiy, K. A., Davatgarzadeh, F., Taheri, M., & Damavand, I. A Review on Fuzzy-Logic Method to Control Robotic Manipulator Systems.
100
 Roper, D. (2013). Energy based control system designs for underactuated robot fish propulsion.
101
 Jiang, S. Y., & Wang, L. X. (2013). Unsupervised Feature Selection Method for Imbalanced Data. Journal of Chinese Computer Systems, 34(1), 63-67.
102
 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.
103
 Jiangsheng Yi, & Wanglian Xi. (2013). Unsupervised feature unbalanced data selection method. Small Computer Systems, 34 (1), 63-66.
104
 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.
105
 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.
106
 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
107
 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.
108
 Jiangsheng Yi, & Wanglian Xi. (2013). Unsupervised feature selection method for imbalanced data. Computer Systems, 34 (1), 63-67.
109
 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).
110
 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.
111
 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).
112
 Wahyunggoro, O., Permanasari, A. E., & Chamsudin, A. Utilization of Neural Network for Disease Forecasting.
113
 Ÿö, Ÿ. Proof Version.
114
 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).
115
 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.
116
 Ivaniuk, D. Neuro-PID Controller for a Pasteurizer.
117
 Lashari, S. A., & Ibrahim, R. (2013). A Framework for Medical Images Classification Using Soft Set. Procedia Technology, 11, 548-556.
118
 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.
119
 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.
120
 Al-Milli, N. (2013). Backpropagation Neural Network for Prediction of Heart Disease. Journal of Theoretical and Applied Information Technology, 56(1), 131-135.
121
 LD, V. A. Simulation of Neuro-PID Controller for Pressure Process.
122
 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.
123
 Lake, D. (2013). Web-Based Expert System for Cattle Diseases Diagnose (Doctoral dissertation, Addis Ababa University).
124
 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.
125
 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.
126
 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.
127
 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.
128
 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.
129
 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.
130
 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.
131
 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.
132
 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.
133
 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.
134
 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.
135
 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).
136
 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.
137
 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.
138
 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.
139
 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.
140
 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.
141
 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.
142
 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.
143
 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.
144
 Chattopadhyay, S. (2013). Mining the risk of heart attack: a comprehensive study. International Journal of Biomedical Engineering and Technology, 11(4), 394-410.
145
 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.
146
 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.
147
 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.
148
 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.
149
 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.
150
 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.
151
 Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
152
 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.
153
 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.
154
 Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141.
155
 Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
156
 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.
157
 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.
158
 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.
159
 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.
160
 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.
161
 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.
162
 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.
163
 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.
164
 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.
165
 Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141.
166
 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.
167
 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.
168
 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
 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.
170
 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.
171
 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.
172
 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.
173
 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.
174
 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.
175
 Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
176
 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.
177
 Seven Tir Ave, S. Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2 nd Order Nonlinear System.
178
 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
 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
 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.
181
 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.
182
 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.
183
 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
 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
 Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
186
 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.
187
 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
 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.
189
 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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 Oliveira, M. A. P. D. (2012). High level coordination and decision making of a simulated robotic soccer team.
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 Sathyanarayana, S. A. S. A Hybrid approach for Named Entity Recognition, Classification and Extraction (NERCE) in Kannada Documents.
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 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.
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