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|Title:||A note on the integration of fuzzy systems with neural networks under a TLTT framework||Authors:||Nie, J.
|Issue Date:||1997||Citation:||Nie, J.,Lee, T.H.,Linkens, D.A. (1997). A note on the integration of fuzzy systems with neural networks under a TLTT framework. Fuzzy Sets and Systems 87 (3) : 277-289. ScholarBank@NUS Repository.||Abstract:||Recently, there has been a considerable amount of interest and practice in combining fuzzy systems with neural networks. Without aiming at giving a thorough review of this field or presenting technical details, this paper tries to provide a unified conceptual framework under which the two types of the systems can be dealt with in a similar manner. We refer to this framework as the two-level-three-term (TLTT) viewpoint. As demonstrated in the paper, this TLTT framework allows us to analyze, discuss, and compare two paradigms in a clear, easy, systematic manner and more importantly provides an informative guideline of how the two paradigms can be better integrated so as to solve the problems at hand; in particular, those problems encountered in engineering fields such as modeling, prediction, classification, and control. © 1997 Elsevier Science B.V.||Source Title:||Fuzzy Sets and Systems||URI:||http://scholarbank.nus.edu.sg/handle/10635/54575||ISSN:||01650114|
|Appears in Collections:||Staff Publications|
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