Optimization of Fuzzy Neural Network based Nonlinear Process System Model using Genetic Algorithm

유전자 알고리즘을 이용한 FNNs 기반 비선형공정시스템 모델의 최적화

In this paper, we proposed an optimazation method using Genetic Algorithm for nonlinear system modeling. Fuzzy Neural Network(FNNs) was used as basic model of nonlinear system. FNNs was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, We used FNNs which was proposed by Yamakawa. The FNNs was composed Simple Inference and Error Back Propagation Algorithm. To obtain optimal model, parameter of membership function, learning rate and momentum coefficient of FNNs are tuned using genetic algorithm. And we used simplex algorithm additionaly to overcome limit of genetic algorithm. For the purpose of evaluation of proposed method, we applied proposed method to traffic choice process and waste water treatment process, and then obtained more precise model than other previous optimization methods and objective model.