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JACIII Vol.3 No.2 pp. 131-135
doi: 10.20965/jaciii.1999.p0131
(1999)

Paper:

Fuzzy Adaptive Search Method for Genetic Programming

Yoichiro Maeda

Faculty of Information Science and Technology, Osaka Electro-Communication University 18-8, Hatsu-cho, Neyagawa, Osaka 572-8530, Japan

Received:
June 11, 1998
Accepted:
November 8, 1998
Published:
April 20, 1999
Keywords:
Genetic programming, Adaptive search, Fuzzy rules, Mutation rate, Crossover rate
Abstract

The greatest problem of genetic programming (GP) is the large amount of calculation. We propose two methods for an efficient GP search – RPGP reducing void searches by pruning redundant nodes in GP and FASGP enabling proper search by tuning a mutation and crossover rate by fuzzy rules. Simulation proved the effectiveness of our proposal.

Cite this article as:
Yoichiro Maeda, “Fuzzy Adaptive Search Method for Genetic Programming,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.2, pp. 131-135, 1999.
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