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JACIII Vol.3 No.4 pp. 320-325
doi: 10.20965/jaciii.1999.p0320
(1999)

Paper:

Moving Genetic Algorithm Based Fuzzy Modeling

Euntai Kim*, Heejin Lee*, Chang-Hoon Lee**, Jung-Hwan Kim**

*Department of Control and Instrumentation Engineer Hankyong National University 67 Sukjung-dong, Ansung, Kyungki, 456-749, Korea

**Department of Electronic Enginerring Yonsei University

Received:
August 10, 1998
Accepted:
September 7, 1998
Published:
August 20, 1999
Keywords:
Fuzzy modeling, Moving genetic algorithm
Abstract

We propose an approach to Takagi-Sugeno fuzzy modeling via a genetic algorithm consisting of 2 tuning steps – coarse and fine. A moving genetic algorithm (MGA) is proposed and used for fine tuning to obtain robust modeling results. Simulation results demonstrate the algorithm’s validity.

Cite this article as:
Euntai Kim, Heejin Lee, Chang-Hoon Lee, and Jung-Hwan Kim, “Moving Genetic Algorithm Based Fuzzy Modeling,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.4, pp. 320-325, 1999.
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Last updated on Feb. 25, 2021