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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 3/2014

01.06.2014 | Original Article

An Atanassov’s intuitionistic fuzzy multi-attribute group decision making method based on entropy and similarity measure

verfasst von: Xia Liang, Cuiping Wei

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 3/2014

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Abstract

In this paper, we propose a new similarity measure for Atanassov’s intuitionistic fuzzy sets by the relationship between entropy and similarity measure. With respect to multi-attribute group decision making problem, we then give an approach to derive the relative importance weights of experts. This approach takes into account decision information from three aspects: the uncertainty degrees of individual expert’s assessing information for alternatives, the similarity degree of the assessing information for alternatives provided by individual expert, and the similarity degree of the individual expert’s assessing information to all the others’. Finally, we establish a method for handling multi-attribute group decision making problem with Atanassov’s intuitionistic fuzzy information, and adopt an illustrative example to demonstrate its rationality and effectiveness.
Vorheriger Artikel A two stages sparse SVM training
Nächster Artikel Hubness-based fuzzy measures for high-dimensional k-nearest neighbor classification

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Metadaten
Titel
An Atanassov’s intuitionistic fuzzy multi-attribute group decision making method based on entropy and similarity measure
verfasst von
Xia Liang
Cuiping Wei
Publikationsdatum
01.06.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 3/2014
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-013-0178-0

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