Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2000.11d
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- Pages.791-793
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- 2000
A study on the novel Neuro-fuzzy network for nonlinear modeling
비선형 모델링에 대한 새로운 뉴로-퍼지 네트워크 연구
- Kim, Dong-Won (School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
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Park, Byoung-Jun
(School of Electrical and Electronic Engineering, Wonkwang Univ.) ;
- Oh, Sung-Kwun (School of Electrical and Electronic Engineering, Wonkwang Univ.)
- Published : 2000.11.25
Abstract
The fuzzy inference system is a popular computing framework based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. The advantage of fuzzy approach over traditional ones lies on the fact that fuzzy system does not require a detail mathematical description of the system while modeling. As modeling method. the Group Method of Data Handling(GMDH) is introduced by A.G. Ivakhnenko GMDH is an analysis technique for identifying nonlinear relationships between system's inputs and output. We study a Novel Neuro-Fuzzy Network (NNFN) in this paper. NNFN is a network resulting from the combination of a fuzzy inference system and polynomial neural network(PNN) (7) which is advanced structure of GMDH. Simulation involve a series of synthetic as well as experimental data used across various neurofuzzy systems.
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