Rule combination in a fuzzy neural network
| dc.citation.epage | 166 | en_US |
| dc.citation.issue | 2 | en_US |
| dc.citation.spage | 161 | en_US |
| dc.citation.volume | 82 | en_US |
| dc.contributor.author | Chen, YJ | en_US |
| dc.contributor.author | Teng, CC | en_US |
| dc.contributor.department | 交大名義發表 | zh_TW |
| dc.contributor.department | 電控工程研究所 | zh_TW |
| dc.contributor.department | National Chiao Tung University | en_US |
| dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
| dc.date.accessioned | 2014-12-08T15:02:22Z | |
| dc.date.available | 2014-12-08T15:02:22Z | |
| dc.date.issued | 1996-09-09 | en_US |
| dc.description.abstract | In this paper, we present a fuzzy neural network (FNN) to realize the rule reasoning of fuzzy inference systems. The proposed fuzzy neural network can acquire the fuzzy rules by employing the learning capability of neural networks. Moreover, for simplifying the structure of the proposed FNN, the redundant rules and linguistic terms are removed from the FNN by means of a rule combination procedure. A sufficient condition related to rule combination is also given. | 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/11536/1042 | |
| dc.identifier.wosnumber | WOS:A1996VD40800004 | |
| dc.language.iso | en_US | en_US |
| dc.subject | fuzzy neural network | en_US |
| dc.subject | fuzzy inference system | en_US |
| dc.subject | rule combination | en_US |
| dc.title | Rule combination in a fuzzy neural network | en_US |
| dc.type | Article; Proceedings Paper | en_US |