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Title: | Reasoning with propositional knowledge based on fuzzy neural logic | Authors: | Wu, W. Teh, H.-H. Yuan, B. |
Issue Date: | May-1996 | 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. | 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. | Source Title: | International Journal of Intelligent Systems | URI: | http://scholarbank.nus.edu.sg/handle/10635/111205 | ISSN: | 08848173 |
Appears in Collections: | Staff Publications |
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