Structure optimization of fuzzy neural network as an expert system using genetic algorithms

Benyamin Kusumo Putro, Ponix Irwanto

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

In this article we developed a method for optimizing the structure of a fuzzy artificial neural networks (FANN) through genetic algorithms. This genetic algorithm (GA) is used by optimizing the number of weight connections in a neural network structure, by the evolution of those structures as individuals in a population. It is found that the optimization of the neural network provides higher confidence accuracy of the suggested solution in a Case Based Diagnostic System. The computational cost of the optimized network also improved considerably high.

Original languageEnglish
Pages (from-to)219-225
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4055
Publication statusPublished - 1 Jan 2000
EventApplications and Science of Computational Intelligence III - Orlando, FL, USA
Duration: 24 Apr 200027 Apr 2000

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