Distance and Similarity Measures for Intuitionistic Hesitant Fuzzy Sets

DOI

10.2991/icaita-16.2016.46How to use a DOI?

Keywords

intuitionistic hesitant fuzzy sets; distance measures; similarity measures; multiple attribute decision making

Abstract

As generalize of the hesitant fuzzy sets, intuitionistic hesitant fuzzy sets (IHFSs), which permits a memberships degree and a non-membership degree of an element to a given set, can be considered as a useful tool to express uncertain information in the human decision making process. Based on the traditional distance measures, such as Euclidean distance, Hamming distance, Hausdorff distance, and other generalized distance measures, in this paper, a variety of distance measures for intuitionistic hesitant fuzzy sets are proposed, based on which the corresponding similarity measures can be obtained. We investigate the connections of the aforementioned distance measures and further develop a number of intuitionistic hesitant ordered weighted distance measures. They can alleviate the influence of unduly large (or small) deviations on the aggregation results by assigning them low (or high) weights. A numerical example is provided to illustrate these distance and similarity measures.

Copyright

© 2016, 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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TY  - CONF
AU  - Xiuming Chen
AU  - Jingming Li
AU  - Li Qian
AU  - Xiande Hu
PY  - 2016/01
DA  - 2016/01
TI  - Distance and Similarity Measures for Intuitionistic Hesitant Fuzzy Sets
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 182
EP  - 186
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.46
DO  - 10.2991/icaita-16.2016.46
ID  - Chen2016/01
ER  -