On the use of fuzzy inference techniques in assessment models: part I--theoretical properties

  • Authors:

  • Kai Meng Tay;Chee Peng Lim

  • Affiliations:

  • Electronic Engineering Department, Faculty of Engineering, University Malaysia Sarawak, Kota Samarahan, Malaysia;School of Electrical and Electronic Engineering, University of Science Malaysia, Minden, Malaysia

  • Venue:
  • Fuzzy Optimization and Decision Making
  • Year:
  • 2008

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Abstract

An assessment model is a mathematical model that produces a measuring index, either in the form of a numerical score or a category to a situation/object, with respect to the subject of measure. From the numerical score, decision can be made and action can be taken. To allow valid and useful comparisons among various situations/objects according to their associated numerical scores to be made, the monotone output property and the output resolution property are essential in fuzzy inference-based assessment problems. We investigate the conditions for a fuzzy assessment model to fulfill the monotone output property 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 its input. This derivative should be greater than the minimum resolution required. From the derivative, we suggest improvements to the output resolution property by refining the fuzzy production rules.