The design of beta basis function neural network and beta fuzzy systems by a hierarchical genetic algorithm

被引：28
作者：
Aouiti, C
Alimi, AM
Karray, F
Maalej, A
机构：
[1] Univ Waterloo, Dept Elect & Comp Engn, PAMI, Pattern Anal & Machine Intelligence Lab, Waterloo, ON N2L 3G1, Canada
[2] Univ 7 Novembre Carthage, Fac Sci Bizerta, Bizerte, Tunisia
[3] Univ Sfax, ENIS, Dept Elect Engn, REGIM,Res Grp Intelligent Machines, Sfax, Tunisia
[4] Univ Sfax, Dept Mech Engn, LASEM, Lab Electromech Syst,ENIS, Sfax, Tunisia
来源：
FUZZY SETS AND SYSTEMS | 2005年 / 154卷 / 02期
关键词：
genetic algorithms; beta function; neural networks; functions approximation; learning; beta fuzzy systems; beta bases function neural networks;
D O I：
10.1016/j.fss.2005.01.013
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We propose an evolutionary method for the design of beta basis function neural networks (BBFNN) and of beta fuzzy systems (BFS). Classical training algorithms start with a predetermined network structure for neural networks and with a predetermined number of fuzzy rules for fuzzy systems. Generally speaking both the neural network and the fuzzy systems are either insufficient or overcomplicated. This paper describes a hierarchical genetic learning model of the BBFNN and the BFS. In order to examine the performance of the proposed algorithm, it is used for functional approximation problem for the case of BBFNN and for the identification of an induction machine fuzzy plant model for the case of BFS. The results obtained have been encouraging. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：251 / 274
页数：24
相关论文
共 50 条
[21]   A genetic algorithm with neural network fitness function evaluation for IMRT beam angle optimization [J].
Dias, Joana ;
Rocha, Humberto ;
Ferreira, Brigida ;
Lopes, Maria do Carmo .
CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH, 2014, 22 (03) :431-455
[22]   A Genetic Algorithm for Designing Neural Network Ensembles [J].
Soares, Symone G. ;
Antunes, Carlos H. ;
Araujo, Rui .
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2012, :681-688
[23]   Fuzzy Optimization on Automobile Final Drive in Hybrid Genetic Algorithm and Neural Network [J].
Xi, Pingyuan ;
Chang, Siqin .
PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND MECHANICS, VOLS 1 AND 2, 2009, :1766-1770
[24]   A genetic algorithm with SOM neural network clustering for multimodal function optimization [J].
Kashtiban, Atabak Mashhadi ;
Khanmohammadi, Sohrab .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (04) :4543-4556
[25]   A Switch Controller Design for the Acrobot Using Neural Network and Genetic Algorithm [J].
Duong, Sam Chau ;
Kinjo, Hiroshi ;
Uezato, Eiho ;
Yamamoto, Tetsuhiko .
2008 10TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION: ICARV 2008, VOLS 1-4, 2008, :1540-+
[26]   Crashworthiness Design for Cylindrical Tube using Neural Network and Genetic Algorithm [J].
Mirzaei, M. ;
Shakeri, M. ;
Sadighi, M. ;
Akbarshahi, H. .
PROCEEDINGS OF THE TWELFTH EAST ASIA-PACIFIC CONFERENCE ON STRUCTURAL ENGINEERING AND CONSTRUCTION (EASEC12), 2011, 14
[27]   Vibrational genetic algorithm enhanced with fuzzy logic and neural networks [J].
Pehlivanoglu, Y. Volkan ;
Baysal, Oktay .
AEROSPACE SCIENCE AND TECHNOLOGY, 2010, 14 (01) :56-64
[28]   Neurofuzzy modeling of chemical process systems with ellipsoidal radial basis function neural networks and genetic algorithms [J].
Schmitz, GPJ ;
Aldrich, C .
COMPUTERS & CHEMICAL ENGINEERING, 1998, 22 :S1001-S1004
[29]   Radial basis function neural network models for power-amplifier design [J].
Xu, GQ ;
Li, MY ;
Xi, YB .
2004 INTERNATIONAL CONFERENCE ON COMMUNICATION, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS - VOL 2: SIGNAL PROCESSING, CIRCUITS AND SYSTEMS, 2004, :1066-1070
[30]   Optimization of neural network topologies using genetic algorithm [J].
Nissinen, AS ;
Koivo, HN ;
Koivisto, H .
INTELLIGENT AUTOMATION AND SOFT COMPUTING, 1999, 5 (03) :211-223
12345