Please use this identifier to cite or link to this item:
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
ISSN: 01650114
Appears in Collections:Staff Publications

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

Page view(s)

checked on Feb 2, 2023

Google ScholarTM


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