DocumentCode :
3164006
Title :
A study on multi-layer fuzzy polynomial inference system based on an extended GMDH algorithm
Author :
Park, Ho Sung ; Oh, Sung Kwun ; Ahn, Tae Chon ; Pedrycz, Witold
Author_Institution :
Div. of Electr. & Electron. Eng., Wonkwang Univ., Iksan, South Korea
Volume :
1
fYear :
1999
fDate :
22-25 Aug. 1999
Firstpage :
354
Abstract :
A new design methodology is proposed to identify the structure and parameters of a fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH (Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN (Fuzzy Polynomial Neural Networks) algorithm uses PNN (Polynomial Neural network) structure and the fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on a consequence of fuzzy rules with polynomial equations such as linear, quadratic and cubic equations. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. We consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of the process model. Several numerical examples are used to evaluate the performance of our proposed model.
Keywords :
fuzzy logic; fuzzy neural nets; identification; inference mechanisms; learning (artificial intelligence); multilayer perceptrons; performance evaluation; polynomials; uncertainty handling; GMDH algorithm; Group Method of Data Handling; PNN; biquadratic polynomial; cubic polynomial; design methodology; fuzzy model; fuzzy polynomial neural network; fuzzy rules; linear polynomial; multilayer fuzzy polynomial inference; neuro-fuzzy architecture; performance evaluation; polynomial neural networks; quadratic polynomial; Design engineering; Equations; Fuzzy sets; Fuzzy systems; Inference algorithms; Least squares approximation; Mathematical model; Neural networks; Polynomials; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
ISSN :
1098-7584
Print_ISBN :
0-7803-5406-0
Type :
conf
DOI :
10.1109/FUZZY.1999.793265
Filename :
793265
Link To Document :
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