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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 4/2018

03.08.2016 | Original Article

Trapezoidal interval type-2 fuzzy aggregation operators and their application to multiple attribute group decision making

verfasst von: Zhiming Zhang

Erschienen in: Neural Computing and Applications | Ausgabe 4/2018

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Abstract

A type-2 fuzzy set, which is characterized by a fuzzy membership function, involves more uncertainties than the type-1 fuzzy set. As the most widely used type-2 fuzzy set, interval type-2 fuzzy set is a very useful tool to model the uncertainty in the process of decision making. As a special case of interval type-2 fuzzy set, trapezoidal interval type-2 fuzzy set can express linguistic assessments by transforming them into numerical variables objectively. The aim of this paper is to investigate the multiple attribute group decision-making problems in which the attribute values and the weights take the form of trapezoidal interval type-2 fuzzy sets. First, we introduce the concept of trapezoidal interval type-2 fuzzy sets and some arithmetic operations between them. Then, we develop several trapezoidal interval type-2 fuzzy aggregation operators for aggregating trapezoidal interval type-2 fuzzy sets and examine several useful properties of the developed operators. Furthermore, based on the proposed operators, we develop two approaches to multiple attribute group decision making with linguistic information. Finally, a practical example is given to illustrate the feasibility and effectiveness of the developed approach.
Vorheriger Artikel Evolutionary framework for coding area selection from cancer data
Nächster Artikel Topological Gaussian ARAM for biologically inspired topological map building

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Metadaten
Titel
Trapezoidal interval type-2 fuzzy aggregation operators and their application to multiple attribute group decision making
verfasst von
Zhiming Zhang
Publikationsdatum
03.08.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2488-0

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