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A note on the integration of fuzzy systems with neural networks under a TLTT framework

✍ Scribed by Junhong Nie; T.H. Lee; D.A. Linkens

Publisher: Elsevier Science
Year: 1997
Tongue: English
Weight: 1000 KB
Volume: 87
Category: Article
ISSN: 0165-0114
DOI: 10.1016/s0165-0114(96)00036-x

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✦ Synopsis

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.

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