Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1998.07b
- /
- Pages.519-521
- /
- 1998
Fuzzy Modeling Schemes Using Messy Genetic Algorithms
메시 유전알고리듬을 이용한 퍼지모델링 방법
- Kwon, Oh-Kook (Dept. of Electrical Engineering, Yonsei University) ;
- Chang, Wook (Dept. of Electrical Engineering, Yonsei University) ;
-
Joo, Young-Hoon
(Dept. of Control and Instrumentation, Kunsan National University) ;
-
Park, Jin-Bae
(Dept. of Electrical Engineering, Yonsei University)
- Published : 1998.07.20
Abstract
Fuzzy inference systems have found many applications in recent years. The fuzzy inference system design procedure is related to an expert or a skilled human operator in many fields. 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. The messy genetic algorithm is used to obtain structurally optimized fuzzy neural network models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the problem of a time series estimation.
Keywords