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https://scholarbank.nus.edu.sg/handle/10635/111205
DC Field | Value | |
---|---|---|
dc.title | Reasoning with propositional knowledge based on fuzzy neural logic | |
dc.contributor.author | Wu, W. | |
dc.contributor.author | Teh, H.-H. | |
dc.contributor.author | Yuan, B. | |
dc.date.accessioned | 2014-11-27T09:45:44Z | |
dc.date.available | 2014-11-27T09:45:44Z | |
dc.date.issued | 1996-05 | |
dc.identifier.citation | Wu, W.,Teh, H.-H.,Yuan, B. (1996-05). Reasoning with propositional knowledge based on fuzzy neural logic. International Journal of Intelligent Systems 11 (5) : 251-265. ScholarBank@NUS Repository. | |
dc.identifier.issn | 08848173 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/111205 | |
dc.description.abstract | In this article, a new kind of reasoning for propositional knowledge, which is based on the fuzzy neural logic initialed by Teh, is introduced. A fundamental theorem is presented showing that any fuzzy neural logic network can be represented by operations: bounded sum, complement, and scalar product. Propositional calculus of fuzzy neural logic is also investigated. Linear programming problems risen from the propositional calculus of fuzzy neural logic show a great advantage in applying fuzzy neural logic to answer imprecise questions in knowledge-based systems. An example is reconsidered here to illustrate the theory. © 1996 John Wiley & Sons, Inc. | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | INSTITUTE OF SYSTEMS SCIENCE | |
dc.description.sourcetitle | International Journal of Intelligent Systems | |
dc.description.volume | 11 | |
dc.description.issue | 5 | |
dc.description.page | 251-265 | |
dc.description.coden | IJISE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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