Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/111280
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dc.titleRule-based reasoning using extended neural logic network
dc.contributor.authorQuah, Tong-Seng
dc.contributor.authorTan, Chew-Lim
dc.contributor.authorTeh, Hoon-Heng
dc.contributor.authorShen, ZuLiang
dc.date.accessioned2014-11-27T09:46:32Z
dc.date.available2014-11-27T09:46:32Z
dc.date.issued1993
dc.identifier.citationQuah, Tong-Seng,Tan, Chew-Lim,Teh, Hoon-Heng,Shen, ZuLiang (1993). Rule-based reasoning using extended neural logic network. Proceedings of the International Joint Conference on Neural Networks 2 : 1405-1408. ScholarBank@NUS Repository.
dc.identifier.isbn0780314212
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/111280
dc.description.abstractNeural Logic Network (NEULONET) are studied in National University of Singapore to incorporate both the pattern processing capability of Multi-layer Perceptrons and the logical inference capability of Boolean Logic Inference Networks within a single frame of neural network environment. In this paper, a few extensions to the NEULONET are proposed. These enhancements to the network structure strengthen its ability to perform rule-based reasonings. The concept of network element (netel) is introduced. With netel, expert system rules may now be easily mapped into rudimentary NEULONETs. The resulting netel knowledge base inherits the semantic meanings of the expert system rules and the learning ability of the connectionist architecture.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentINFORMATION SYSTEMS & COMPUTER SCIENCE
dc.contributor.departmentINSTITUTE OF SYSTEMS SCIENCE
dc.description.sourcetitleProceedings of the International Joint Conference on Neural Networks
dc.description.volume2
dc.description.page1405-1408
dc.description.coden85OFA
dc.identifier.isiutNOT_IN_WOS
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