Chaos optimization algorithm design for fuzzy neural network
ZOU En
LI Xiang-fei
ZHANG Tai-shan
Abstract：An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network. Offline optimization uses chaos algorithm and chaos variables are applied to search for network structure and parameters, in which the network is in dynamic chaos state. An approximate optimal network structure and parameters are found from dynamic network according to performance index. On-line optimization uses gradient descent algorithm and the initial values of gradient descent searching are parameters approximately global optimal values from chaos searching, the parameters of fuzzy neural network are further adjusted. The global optimal values of network are searched quickly by means of combination of chaos global searching and gradient descent local searching. Finally, second order delay system is simulated, and the results show that the chaos optimal control is of high precision, small overshoot, fast response and good robustness.
Keywords：fuzzy neural networkoptimizationchaotic variablesgradient descent algorithm
Publication Date：2005-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 578-582 )