A genetic algorithm based fuzzy-tuned neural network

Author

Ling, S.H. ; Lam, H.K. ; Leung, F.H.F. ; Lee, Y.S.

Author_Institution

Centre for Multimedia Signal Process., Hong Kong Polytech. Univ., Kowloon, China

Volume

1

fYear

2003

Firstpage

220

Abstract

This paper presents a fuzzy-tuned neural network, which is trained by the genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a novel neuron model with two activation functions is employed. The parameters of the proposed network are tuned by GA with arithmetic crossover and non-uniform mutation. Some application examples are given to illustrate the merits of the proposed network.

Keywords

fuzzy logic; fuzzy neural nets; genetic algorithms; learning (artificial intelligence); pattern recognition; activation functions; arithmetic crossover; fuzzy-tuned neural network; genetic algorithm; modified neural network; neural-fuzzy network; neuron model; nonuniform mutation; parameters training; pattern recognition; sunspot number forecasting; synaptic connection weight; Arithmetic; Feedforward neural networks; Feedforward systems; Fuzzy neural networks; Genetic algorithms; Genetic engineering; Genetic mutations; Neural networks; Neurons; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on

Print_ISBN

0-7803-7810-5

Type

conf

DOI

10.1109/FUZZ.2003.1209365

Filename

1209365