DocumentCode
304065
Title
Solving fuzzy regression equations using a fuzzy neural network
Author
Blount, Michael ; Lin, Chiahung ; Duckstein, Lucien
Author_Institution
Dept. of Syst. & Ind. Eng., Arizona Univ., Tucson, AZ, USA
Volume
2
fYear
1996
fDate
8-11 Sep 1996
Firstpage
1161
Abstract
Fuzzy linear regression (FLR) and fuzzy least squares (FLS) involve solving a system of linear fuzzy equations. A fuzzy neural network (FNN) using symmetric triangular fuzzy numbers appears to solve such systems of linear fuzzy equations using a backward error propagation algorithm. This FNN method is then compared to standard FLR and FLS methods on two sample problems; it appears to perform at least as well
Keywords
fuzzy neural nets; fuzzy set theory; learning (artificial intelligence); least squares approximations; statistical analysis; backward error propagation algorithm; fuzzy least squares; fuzzy linear regression; fuzzy neural network; fuzzy regression equations; linear fuzzy equations; symmetric triangular fuzzy numbers; Equations; Fuzzy neural networks; Fuzzy systems; Industrial engineering; Least squares methods; Linear regression; Measurement standards; Neural networks; Neurons; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location
New Orleans, LA
Print_ISBN
0-7803-3645-3
Type
conf
DOI
10.1109/FUZZY.1996.552341
Filename
552341
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