DocumentCode
344705
Title
Cascading fuzzy neural networks
Author
Duan, Ji-Cheng ; Chung, Fu-lai
Author_Institution
Dept. of Comput., Hong Kong Polytech., Kowloon, Hong Kong
Volume
1
fYear
1999
fDate
22-25 Aug. 1999
Firstpage
55
Abstract
A new fuzzy neural network (FNN) model based on syllogistic fuzzy reasoning is proposed. Unlike most of the proposed FNN models which implement single-stage fuzzy reasoning mechanisms, the new model implements syllogistic fuzzy reasoning which is usually used by human beings. A hybrid learning algorithm is presented to derive an appropriate syllogistic fuzzy rule set and update the corresponding network parameters. It is found that the model is superior to its single-stage counterpart in learning ability and robustness.
Keywords
fuzzy logic; fuzzy neural nets; fuzzy set theory; genetic algorithms; inference mechanisms; learning (artificial intelligence); fuzzy neural network; fuzzy rule set; genetic algorithms; hybrid learning algorithm; syllogistic fuzzy reasoning; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Genetic algorithms; Humans; Neural networks; Roads; Robustness;
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.1999.793206
Filename
793206
Link To Document