Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/54575
Title: A note on the integration of fuzzy systems with neural networks under a TLTT framework
Authors: Nie, J.
Lee, T.H. 
Linkens, D.A.
Keywords: Engineering applications
Fuzzy systems
Fuzzy-neural systems
Neural networks
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

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.