Distance and Similarity Measures for Intuitionistic Hesitant Fuzzy Sets
- 10.2991/icaita-16.2016.46How to use a DOI?
- intuitionistic hesitant fuzzy sets; distance measures; similarity measures; multiple attribute decision making
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.
- © 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/).
Cite this article
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 -