caa a22 4500 606159134 CHVBK 20210128100623.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00521-014-1797-4 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1797-4 Learning Fuzzy Cognitive Maps using Imperialist Competitive Algorithm [Elektronische Daten] [Sadra Ahmadi, Nafiseh Forouzideh, Somayeh Alizadeh, Elpiniki Papageorgiou] In this paper, a new automated Fuzzy Cognitive Maps (FCMs) learning algorithm is developed to generate FCMs from historical data. Automated FCM learning algorithms are used to model and analyze systems which are very complex and cannot be handled by experts' knowledge. The algorithm developed in this paper is based on the Imperialist Competitive Algorithm for global optimization and is called the Imperialist Competitive Learning Algorithm (ICLA). The ICLA divides the search space into several sections. It extracts the best knowledge from each section and follows a procedure to avoid local optima alongside rapid learning. Experiments have been conducted to compare the ICLA with other well-known FCM learning algorithms. The results show that in most cases, the ICLA performs better for learning FCMs in terms of solution accuracy and execution time. The testing results show clearly that the ICLA is a robust, fast and accurate FCM learning algorithm. The Natural Computing Applications Forum, 2014 Fuzzy Cognitive Maps (FCMs) nationallicence Imperialist Competitive Algorithm (ICA) nationallicence FCM learning nationallicence Ahmadi Sadra Faculty of Information Technology, Monash University, 3800, Clayton, VIC, Australia aut Forouzideh Nafiseh Faculty of Engineering, Monash University, 3800, Clayton, VIC, Australia aut Alizadeh Somayeh Department of IT, Faculty of Industrial Engineering, K.N.Toosi University, Shahid Agahi Alley- Dabestan Street- Resalat Expressway- Seyed Khandan, 1631714191, Tehran, Iran aut Papageorgiou Elpiniki Department of Computer Engineering, Technological Education Institute (TEI) of Central Greece, 3rd Km Old National Road Lamia-Athens, 35100, Lamia, Greece aut Neural Computing and Applications Springer London 26/6(2015-08-01), 1333-1354 0941-0643 26:6<1333 2015 26 521 https://doi.org/10.1007/s00521-014-1797-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1797-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ahmadi Sadra Faculty of Information Technology, Monash University, 3800, Clayton, VIC, Australia aut NATIONALLICENCE 700 1- Forouzideh Nafiseh Faculty of Engineering, Monash University, 3800, Clayton, VIC, Australia aut NATIONALLICENCE 700 1- Alizadeh Somayeh Department of IT, Faculty of Industrial Engineering, K.N.Toosi University, Shahid Agahi Alley- Dabestan Street- Resalat Expressway- Seyed Khandan, 1631714191, Tehran, Iran aut NATIONALLICENCE 700 1- Papageorgiou Elpiniki Department of Computer Engineering, Technological Education Institute (TEI) of Central Greece, 3rd Km Old National Road Lamia-Athens, 35100, Lamia, Greece aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/6(2015-08-01), 1333-1354 0941-0643 26:6<1333 2015 26 521