DocumentCode :
3385837
Title :
The fuzzy neural networks based on evolutionary programming
Author :
Liu Fang
Author_Institution :
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
Volume :
2
fYear :
2009
fDate :
28-29 Nov. 2009
Firstpage :
449
Lastpage :
452
Abstract :
In this paper, a approach for automatically generating fuzzy rules from sample patterns is presented. Then a self-adaptive fuzzy neural network is built based on evolutionary computation. The salient characteristics of the self-adaptive fuzzy neural networks are:1. structure identification and parameters estimation are performed automatically and simultaneously; 2.fuzzy rules can be recruited or deleted dynamically by evolutionary computation; 3.parameters of rules can be obtained by evolutionary computation. Simulation results demonstrate that a compact and high performance fuzzy rule base can be constructed. Comprehensive comparisons with other approach show that the proposed approach is superior over other in terms of learning efficiency and performance.
Keywords :
data mining; evolutionary computation; fuzzy neural nets; parameter estimation; evolutionary computation; evolutionary programming; fuzzy rules; parameters estimation; self-adaptive fuzzy neural network; structure identification; Computational intelligence; Evolutionary computation; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Genetic programming; Input variables; Neural networks; evolutionary programming; fuzzy neural networks; fuzzy rule;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4606-3
Type :
conf
DOI :
10.1109/PACIIA.2009.5406561
Filename :
5406561
Link To Document :
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