한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)
- 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
- /
- Pages.252-256
- /
- 1997
메시 유전 알고리듬을 이용한 퍼지 규칙 동정
Fuzzy Rule Identification Using Messy Genetic Algorithm
- 발행 : 1997.10.01
초록
The success of a fuzzy neural network(FNN) control system solving any given problem critically depends on the architecture of the network. Various attempts have been made in optimizing its structure using genetic algorithm automated designs. This paper presents a new approach to structurally optimized designs of FNN models. A messy genetic algorithm is used to obtain structurally optimized FNN models. Structural optimization is regarded important before neural networks based learning is switched into. We have applied the method to the problem of a numerical approximation