Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.07d
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- Pages.3004-3006
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- 2000
Fuzzy-Neural Networks with Parallel Structure and Its Application to Nonlinear Systems
병렬구조 FNN과 비선형 시스템으로의 응용
- Park, Ho-Sung (School of Electrical & Electronic Engineering, Wonkwang Univ.) ;
- Yoon, Ki-Chan (School of Electrical & Electronic Engineering, Wonkwang Univ.) ;
- Oh, Sung-Kwun (School of Electrical & Electronic Engineering, Wonkwang Univ.)
- Published : 2000.07.17
Abstract
In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.
Keywords