Deakin University
Browse

File(s) under permanent embargo

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

conference contribution
posted on 2008-01-01, 00:00 authored by K Tay, Chee Peng Lim, C Teh
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.

History

Event

Cybernetic Intelligent Systems. Conference (7th : 2008 : London, England)

Publisher

IEEE

Location

London, England

Place of publication

Piscataway, N. J.

Start date

2008-09-09

End date

2008-09-10

ISBN-13

9781424429158

ISBN-10

1424429153

Language

eng

Publication classification

E1.1 Full written paper - refereed

Title of proceedings

CIS 2008 : Proceedings of the 7th IEEE International Conference on Cybernetic Intelligent Systems