Browsing by Author "SHANN, JJ"

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A FUZZY NEURAL-NETWORK FOR RULE ACQUIRING ON FUZZY CONTROL-SYSTEMS
(1995-05-12)
SHANN, JJ
;
FU, HC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
This paper presents a layer-structured fuzzy neural network (FNN) for learning rules of fuzzy-logic control systems. Initially, FNN is constructed to contain all the possible fuzzy rules. We propose a two-phase learning procedure for this network. The first phase is a error-backprop (EBP) training, and the second phase is a rule pruning. Since some functions of the nodes in the FNN have the competitive characteristics, the EBP training will converge quickly. After the training, a pruning process is performed to delete redundant rules for obtaining a concise fuzzy rule base. Simulation results show that for the truck backer-upper control problem, the training phase learns the knowledge of fuzzy rules in several dozen epochs with an error rate of less than 1%. Moreover, the fuzzy rule base generated by the pruning process contains only 14% of the initial fuzzy rules and is identical to the target fuzzy rule base.
BACKPROPAGATION LEARNING FOR ACQUIRING FINE KNOWLEDGE OF FUZZY NEURAL NETWORKS
(1993)
SHANN, JJ
;
FU, HC
;
資訊工程學系
;
Department of Computer Science
KNOWLEDGE LEARNING ON FUZZY EXPERT NEURAL NETWORKS
(1994)
FU, HC
;
SHANN, JJ
;
PAO, HT
;
資訊工程學系
;
Department of Computer Science