제어로봇시스템학회:학술대회논문집
- 2001.10a
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- Pages.71.2-71
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- 2001
Nonlinear System Modelling Using Neural Network and Genetic Algorithm
- Kim, Hong-Bok (Korea Maritime Univ.) ;
- Kim, Jung-Keun (Korea Maritime Univ.) ;
- Hwang, Seung-Wook (Korea Maritime Univ.) ;
- Ha, Yun-Su (Korea Maritime Univ.) ;
- Jin, Gang-Gyoo (Korea Maritime Univ.)
- Published : 2001.10.01
Abstract
This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...
Keywords