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zhuozhuokankan新虫 (初入文坛)
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[求助]
请大家帮忙检索一篇论文
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Title: Premise Reduction of Fuzzy Inference Based on Hierarchical Variable Weights Author: Yuzhuo Zhang 期刊名称 ： ICIC Express Letters |
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Accession number: 20163702800915 Title: Premise reduction of fuzzy inference based on hierarchical variable weights Authors: Zhang, Yuzhuo1 Email author zhangyuzhuo@uibe.edu.cn Author affiliation: 1 School of Statistics, University of International Business and Economics, No. 10, Huixin Dongjie, Chaoyang District, Beijing; 100029, China Corresponding author: Zhang, Yuzhuo (zhangyuzhuo@uibe.edu.cn) Source title: ICIC Express Letters Abbreviated source title: ICIC Express Lett. Volume: 10 Issue: 9 Issue date: September 1, 2016 Publication year: 2016 Pages: 2149-2156 Language: English ISSN: 1881803X Document type: Journal article (JA) Publisher: ICIC Express Letters Office Abstract: In this paper, we analyze some problems existing in rule premise reduction of multidimensional fuzzy inference, and propose a new premise reduction method based on hierarchical variable weights in factor space theory, which not only shows relative importance of antecedent components in fuzzy inference, but considers different preference requirements of decision makers. In addition, it is proved that the reduction of rule premises does not change the interpolation approximation of the fuzzy systems constructed by the improved CRI (Compositional Rule of Inference). An illustrative example shows that the proposed premise reduction method is practicable and effective. © 2016 ICIC International. Number of references: 23 Main heading: Fuzzy inference Controlled terms: Decision making - Decision theory - Fuzzy systems - Hierarchical systems Uncontrolled terms: Compositional rule of inferences - Decision makers - Factor space - Hierarchical variables - Reduction method Classification code: 721.1Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 912.2Management - 961Systems Science Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. Full-text and Local Holdings Links |
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