DocumentCode
2365080
Title
The application of fuzzy set and neural network in system identification and classification
Author
Goh, K.B. ; Chiang, W.-L.
Author_Institution
Dept. of Civil Eng., Nat. Central Univ.
fYear
1993
fDate
25-28 Apr 1993
Firstpage
145
Lastpage
152
Abstract
Outlines a new learning algorithm to deal with interval information for a feedforward neural network. From the concept of fuzzy sets and using the vertex method, a new backpropagation neural network, called virtual vertex backpropagation, VVBP, is presented. A dynamic tracing machine is introduced to overcome weight correction in the learning process. Two applications in simple system identification and pattern classification are presented to discuss the effectiveness of VVBP
Keywords
backpropagation; feedforward neural nets; fuzzy neural nets; identification; pattern classification; dynamic tracing machine; feedforward neural network; fuzzy sets; interval information; learning algorithm; pattern classification; system identification; vertex method; virtual vertex backpropagation; weight correction; Feedforward neural networks; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Information processing; Intelligent networks; Machine learning; Neural networks; Neurons; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Uncertainty Modeling and Analysis, 1993. Proceedings., Second International Symposium on
Conference_Location
College Park, MD
Print_ISBN
0-8186-3850-8
Type
conf
DOI
10.1109/ISUMA.1993.366776
Filename
366776
Link To Document