International Journal of Computational Intelligence Systems

Volume 6, Issue 5, September 2013, Pages 987 - 1001

New Entropy, Similarity Measure of Intuitionistic Fuzzy Sets and their Applications in Group Decision Making

Authors
Xia Liang, Cuiping Wei, Meimei Xia
Corresponding Author
Cuiping Wei
Received 15 March 2012, Accepted 16 August 2012, Available Online 1 September 2013.
DOI
10.1080/18756891.2013.809939How to use a DOI?
Keywords
multi-attribute group decision making, intuitionistic fuzzy sets, entropy, similarity measure
Abstract

In this paper, we propose a new entropy measure with geometrical interpretation of intuitionistic fuzzy sets. Compared with the entropy measure provided by Szmidt and Kacprzyk, the new entropy formula in this paper can measure both fuzziness and intuitionism for intuitionistic fuzzy sets. According to the relationship between entropy and similarity measure, we construct a new similarity measure for intuitionistic fuzzy sets. Then we present two methods, based on entropy and similarity measure, to determine weights of experts for multi-attribute group decision making with intuitionistic fuzzy information.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
6 - 5
Pages
987 - 1001
Publication Date
2013/09/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2013.809939How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Xia Liang
AU  - Cuiping Wei
AU  - Meimei Xia
PY  - 2013
DA  - 2013/09/01
TI  - New Entropy, Similarity Measure of Intuitionistic Fuzzy Sets and their Applications in Group Decision Making
JO  - International Journal of Computational Intelligence Systems
SP  - 987
EP  - 1001
VL  - 6
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.809939
DO  - 10.1080/18756891.2013.809939
ID  - Liang2013
ER  -