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Proceedings Paper

Structure optimization of fuzzy neural network as an expert system using genetic algorithms
Author(s): Benyamin Kusumoputro; Ponix Irwanto
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Paper Abstract

In this article we developed a method for optimizing the structure of a fuzzy artificial neural networks through genetic algorithms. This genetic algorithm 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.

Paper Details

Date Published: 30 March 2000
PDF: 7 pages
Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380573
Show Author Affiliations
Benyamin Kusumoputro, Univ. of Indonesia (Indonesia)
Ponix Irwanto, Univ. of Indonesia (Indonesia)

Published in SPIE Proceedings Vol. 4055:
Applications and Science of Computational Intelligence III
Kevin L. Priddy; Paul E. Keller; David B. Fogel, Editor(s)

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