Fuzzy rule base assessment models : theoretical analyses and a case study

Tay, Kai Meng, Lim, Chee Peng and Teh, Chee Siong 2008, Fuzzy rule base assessment models : theoretical analyses and a case study, in CIS 2008 : Proceedings of the 7th IEEE International Conference on Cybernetic Intelligent Systems, IEEE, Piscataway, N. J..

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Title Fuzzy rule base assessment models : theoretical analyses and a case study
Author(s) Tay, Kai Meng
Lim, Chee Peng
Teh, Chee Siong
Conference name Cybernetic Intelligent Systems. Conference (7th : 2008 : London, England)
Conference location London, England
Conference dates 9-10 Sept. 2008
Title of proceedings CIS 2008 : Proceedings of the 7th IEEE International Conference on Cybernetic Intelligent Systems
Editor(s) [Unknown]
Publication date 2008
Conference series Cybernetic Intelligent Systems. Conference
Total pages 6
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) cognitive science
failure analysis
fuzzy systems
humans
mathematical model
predictive models
risk analysis
risk management
time measurement
virtual manufacturing
Summary An assessment model is usually a mathematical model that produces a measuring index, in the form of a numerical score to a situation/object, with respect to the subject of measure. To allow a valid and useful comparison among various situations/objects according to their associated numerical scores to be made, two important properties, i.e., the monotone output property and output resolution properties, are essential in fuzzy inference-based assessment problems. In this paper, the conditions for a fuzzy assessment model to fulfill the monotone output property is investigated using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to the input, whereby the derivative should be greater than a minimum resolution. Based on the derivative, improvements to the output resolution property by refining the fuzzy production rules are suggested. A case study on the Bowles fuzzy RPN model to demonstrate the effectiveness of the properties is also included.
ISBN 1424429153
9781424429158
Language eng
Field of Research 109999 Technology not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048728

Document type: Conference Paper
Collection: Institute for Frontier Materials
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