On the entropy for Atanassov's intuitionistic fuzzy sets: An interpretation from the perspective of amount of knowledge

被引：0
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作者：
Guo, Kaihong [1 ]
Song, Qi [1 ]
机构：
[1] School of Information, Liaoning University, Shenyang,110036, China
来源：
Applied Soft Computing Journal | 2014年 / 24卷
关键词：
Given the fact that totally unknown information cannot be expressed by Zadeh's fuzzy sets but can well be represented by Atanassov's intuitionistic fuzzy sets (A-IFSs); we provide in this paper a new idea; from the perspective of amount of knowledge; that the entropy for such information should be unique so that it may differ significantly from the entropy of a particular fuzzy element of which the membership and non-membership values are both equal to 0.5. Motivated by this idea; we present a more strict axiomatic definition of entropy on A-IFSs; and then develop a new entropy measure of A-IFSs that satisfies the refined axioms; with the aim of overcoming some drawbacks and ambiguities the existing entropy brings about and building a new entropy measurement model in the A-IFSs context to show some unique features of A-IFSs from the viewpoint of a specific purpose; notably those related to decision making. This allows us to capture the intrinsic amount of knowledge and the additional features that may be relevant when making decisions; and ultimately may be able to help us distinguish such particular cases in which the membership values are equal to the corresponding non-membership values in the A-IFSs context. Finally; a real-life example is provided for an in-depth discussion on the application of the developed models in decision making under uncertainty. © 2014 Elsevier B.V. All rights reserved;
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页码：328 / 340
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