DocumentCode :
1750587
Title :
Fuzzy regression analysis by a fuzzy neural network and its application to dual response optimization
Author :
Cheng, Chi-Bin
Author_Institution :
Dept. of Ind. Eng. & Manage., Chao-Yang Univ. of Technol., Taichung, Taiwan
fYear :
2001
fDate :
25-28 July 2001
Firstpage :
2681
Abstract :
Fuzzy regression analysis achieved by a fuzzy radial basis function neural network is discussed in this paper. A fuzzy regression model constructed in such a manner is then applied to a dual-response optimization problem. Fuzzy regression models are ideally suited for dual-response optimization with two advantages: (1) many systems encountered in practice are fuzzy, and (2) fuzzy regression models have dual responses in nature. The dual response optimization problem is formulated as a multiple-objective decision-making program, and an algorithm based on the duality theory is developed to solve this problem. A numerical example is also provided for illustration
Keywords :
decision theory; duality (mathematics); fuzzy neural nets; fuzzy systems; mathematical programming; mathematics computing; operations research; radial basis function networks; statistical analysis; dual response optimization; duality theory; fuzzy radial basis function neural network; fuzzy regression analysis; fuzzy systems; multiple-objective decision-making programming; Chaos; Design optimization; Engineering management; Fuzzy neural networks; Fuzzy systems; Humans; Industrial engineering; Radial basis function networks; Regression analysis; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
Type :
conf
DOI :
10.1109/NAFIPS.2001.943647
Filename :
943647
Link To Document :
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