Journal
APPLIED INTELLIGENCE
Volume 22, Issue 3, Pages 219-232Publisher
SPRINGER
DOI: 10.1007/s10791-005-6620-5
Keywords
prioritized information fusion algorithm; generalized fuzzy numbers; similarity measures; information filtering; prioritized operator
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Although Yager has presented a prioritized operator for fuzzy subsets, called the non-monotonic operator, it can not be used to deal with multi-criteria fuzzy decision-making problems when generalized fuzzy numbers are used to represent the evaluating values of criteria. In this paper, we present a prioritized information fusion algorithm based on the similarity measure of generalized fuzzy numbers. The proposed prioritized information fusion algorithm has the following advantages: (1) It can handle prioritized multi-criteria fuzzy decision-making problems in a more flexible manner due to the fact that it allows the evaluating values of criteria to be represented by generalized fuzzy numbers or crisp values between zero and one, and (2) it can deal with prioritized information filtering problems based on generalized fuzzy numbers.
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