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


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

June 11, 1998
November 8, 1998
April 20, 1999
Genetic programming, Adaptive search, Fuzzy rules, Mutation rate, Crossover rate
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:
Y. 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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