Fuzzified genetic algorithm with prefiltering for adaptive optimization

Jeongdal Kim; Andrew A. Kostrzewski; Dai Hyun Kim; Judy Chen; Anatoly A. Vasiliev; Gajendra D. Savant; Tomasz P. Jannson

doi:10.1117/12.284217

13 October 1997 Fuzzified genetic algorithm with prefiltering for adaptive optimization

Jeongdal Kim, Andrew A. Kostrzewski, Dai Hyun Kim, Judy Chen, Anatoly A. Vasiliev, Gajendra D. Savant, Tomasz P. Jannson

Author Affiliations +

Proceedings Volume 3165, Applications of Soft Computing; (1997) https://doi.org/10.1117/12.284217
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Genetic algorithm performance has been improved by adaptively modifying genetic operators, and by filtering out recurring chromosomes from the fitness evaluation process. The enhanced genetic algorithm has been applied to neural network topology selection and function optimization. The performance of the algorithm was evaluated in multiple function and problem domains, where it showed superior convergence speed.

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Jeongdal Kim, Andrew A. Kostrzewski, Dai Hyun Kim, Judy Chen, Anatoly A. Vasiliev, Gajendra D. Savant, and Tomasz P. Jannson "Fuzzified genetic algorithm with prefiltering for adaptive optimization", Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); https://doi.org/10.1117/12.284217

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