Title :
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
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;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1209365
