IMPLEMENTATION OF A FUZZY INFERENCE SYSTEM USING A NORMALIZED FUZZY NEURAL-NETWORK
| dc.citation.epage | 31 | en_US |
| dc.citation.issue | 1 | en_US |
| dc.citation.spage | 17 | en_US |
| dc.citation.volume | 75 | en_US |
| dc.citation.woscount | 21 | |
| dc.contributor.author | CHAO, CT | en_US |
| dc.contributor.author | TENG, CC | en_US |
| dc.contributor.department | 電控工程研究所 | zh_TW |
| dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
| dc.date.accessioned | 2014-12-08T15:03:07Z | |
| dc.date.available | 2014-12-08T15:03:07Z | |
| dc.date.issued | 1995-10-13 | en_US |
| dc.description.abstract | In this paper, we present a normalized fuzzy neural network (NFNN) to implement fuzzy inference systems. The proposed NFNN architecture makes an effective rule combination technique possible and thus enables us to significantly reduce the number of rules in the NFNN. We also derive a sufficient condition for rule combination and provide an algorithm to perform rule combination. Simulation results show that when combined with a rule elimination method the proposed rule combination method can greatly reduce the number of rules in the NFNN. | en_US |
| dc.identifier.issn | 0165-0114 | en_US |
| dc.identifier.journal | FUZZY SETS AND SYSTEMS | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/1699 | |
| dc.identifier.wosnumber | WOS:A1995RU52400002 | |
| dc.language.iso | en_US | en_US |
| dc.subject | FUZZY INFERENCE SYSTEM | en_US |
| dc.subject | FUZZY NEURAL NETWORK | en_US |
| dc.subject | RULE COMBINATION | en_US |
| dc.title | IMPLEMENTATION OF A FUZZY INFERENCE SYSTEM USING A NORMALIZED FUZZY NEURAL-NETWORK | en_US |
| dc.type | Article | en_US |