Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33170
Title: Incorporating machine intelligence in a parameter-based control systema: a neural-fuzzy approach
Authors: Lau, HCW
Wong, TT
Ning, A
Keywords: Fuzzy logic
Heat transfer
Machine intelligence
Neural network
Issue Date: 2001
Publisher: Elsevier Sci Ltd
Source: Artificial intelligence in engineering, 2001, v. 15, no. 3, p. 253-264 How to cite?
Journal: Artificial Intelligence in Engineering 
Abstract: The capabilities of the two computational intelligence technologies including neural network and fuzzy logic can be synergized through the formation of an integrated and unified model which capitalizes on the benefits and concurrently offsets the flaws of the involved technologies. In this paper, a neural-fuzzy model, which is characterized by its ability to suggest the appropriate change of process parameters in a relatively complex parameter-based control situation involving multiple parameters, is presented. This model is particularly useful in multiple input and multiple output situations where complex mathematical calculations are required if conventional control approach is adopted. In particular, it serves to acquire knowledge from the information base for extracting rules, which are then fuzzified based on fuzzy principle. To validate the feasibility of this approach, a test has been conducted based on the neural-fuzzy model with the objective to achieve heat transfer enhancement in rectangular ducts using transverse ribs. This paper describes the roadmap for the deployment of this hybrid model to enhance machine intelligence of a complex system with the description of a case study to exemplify its underlying principles.
URI: http://hdl.handle.net/10397/33170
ISSN: 0954-1810
DOI: 10.1016/S0954-1810(01)00020-6
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

8
Last Week
0
Last month
0
Citations as of Dec 9, 2017

WEB OF SCIENCETM
Citations

6
Last Week
0
Last month
0
Citations as of Nov 18, 2017

Page view(s)

37
Last Week
1
Last month
Checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric



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