International Computer Science and Engineering Society (ICSES) |
ICSES Transactions on Neural and Fuzzy Computing
Vol. 2, No. 2, Jun. 2019 An Overview on Hesitant Fuzzy Information Measures | Short Letter
a Quchan University of Technology, Quchan, Iran
Corresponding Author Affiliation: Quchan University of Technology, Quchan, Iran Tel: +989155280519 E-mail: bfarhadinia@qiet.ac.ir 2nd e-mail: bahramfarhadinia@yahoo.com
Highlights and Novelties
2- We are going to give a thorough and systematic review of similarity measures for HFSs. 3- We are going to give a thorough and systematic review of entropy measures for HFSs. Manuscript Abstract
Although the concept of fuzzy set (FS) has been widely and successfully applied in many different areas to model some types of uncertainty, the limitation of this concept is still more serious in case of dealing with imprecise and vague information when different sources of vagueness appear simultaneously. Due to this fact and to overcome such limitations, a number of extensions of FSs have been introduced in the literature. By the way, among the most known extensions of FSs, hesitant fuzzy set (HFS) has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as decision making, aggregation operators, and information measures. Because of such a growth, throughout the present manuscript, we are going to give a thorough and systematic review to the main research results in the field of information measures for HFSs including the distance measures, the similarity measures, and the entropy measures. What seems more considerable in this study is the systematic transformation of the distance measure into the similarity measure and vice versa, and moreover, the two categories of entropy measures including those are derived from the other information measures, and those are based on axiomatic frameworks. Keywords
Hesitant fuzzy set Distance measure Similarity measure Entropy measure Copyright
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. Cite this manuscript as
Bahram Farhadinia, "An Overview on Hesitant Fuzzy Information Measures," ICSES Transactions on Neural and Fuzzy Computing (ITNFC), vol. 2, no. 2, pp. 22-27, Jun. 2019. For External Scientific Databeses
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