A Design for a Self-Organising Fuzzy Neural Network Based on the Genetic Algortihm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A novel hybrid algorithm based on the genetic algorithm, named self-organizing fuzzy neural network based on genetic algorithm (SOFNNGA), is proposed to design a fuzzy neural network to implement Takagi- Sugeno (TS) type fuzzy models in this paper. A new adding method based on geometric growing criterion and the å-completeness of fuzzy rules is used to generate the initial structure firstly. Then a hybrid algorithm based on genetic algorithms, backpropagation, and recursive least squares estimation is used to adjust all parameters, which has two steps: first, adjusting the parameter matrix, and second, centers and widths of all membership functions are modified. A simulation for a benchmark problem is presented to illustrate the performance of the proposed algorithm.
Original languageEnglish
Title of host publicationUnknown Host Publication
Pages1967-1972
Number of pages6
Publication statusPublished - Oct 2003
Event2003 IEEE Int. Conf. Systems Man and Cybernetics - Washington, DC, USA
Duration: 1 Oct 2003 → …

Conference

Conference2003 IEEE Int. Conf. Systems Man and Cybernetics
Period1/10/03 → …

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