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22.10.2016 | Methodologies and Application

New distance measures on hesitant fuzzy sets based on the cardinality theory and their application in pattern recognition

verfasst von: Fangwei Zhang, Shuyan Chen, Jianbo Li, Weiwei Huang

Erschienen in: Soft Computing | Ausgabe 4/2018

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Abstract

As a generalization of fuzzy set, hesitant fuzzy set (HFS) permits the membership of an element to a set having a set of possible values. Distance is one of important tools in measuring the relationship between two HFSs. Based on the cardinality theory, some novel distances which take the cardinal numbers of HFSs into account have been introduced using the concept of “multi-sets.” The main advantage of the distance measures is that they can more objectively and universally measure the relationship between HFSs than the existing methods. Finally, the performance of the proposed distance measures is illustrated through two pattern recognition examples in port enterprise management and transportation infrastructure construction.

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Titel: New distance measures on hesitant fuzzy sets based on the cardinality theory and their application in pattern recognition
verfasst von: Fangwei Zhang
Shuyan Chen
Jianbo Li
Weiwei Huang
Publikationsdatum: 22.10.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 4/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-016-2411-8

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