About premise reduction of fuzzy inference algorithm

Cheng-yi Zhang (), Qi Niu, Peng De-jun and Juan Li
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Cheng-yi Zhang: Hainan Normal University
Qi Niu: Zhumadian Education College
Peng De-jun: Hainan Normal University
Juan Li: Hainan Normal University

Fuzzy Information and Engineering, 2009, vol. 1, issue 3, 247-257

Abstract: Abstract The comprehensive model with “weighted-objective nearness degree” is introduced in the process of multi-objective decision-making, by which a reduction problem of inference antecedents is studied in traditional fuzzy inference method. Moreover, based on the comprehensive model with “weighted-objective nearness degree”, SMTT fuzzy inference algorithm is proposed. This algorithm not only shows the relative importance of every antecedent component in fuzzy inference, but also considers the influence of nearness degree between every antecedent component’s evaluation and inference objective on inference conclusions. The enactment of inference objective reflects the preference degree of decision maker to every antecedent component’s evaluation. Therefore, it is much fitter for the demands of practical inference.

Keywords: Fuzzy inference; SMTT fuzzy inference algorithm; Weighted-objective nearness degree (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/s12543-009-0019-8

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