A new concept of Cosine similarity measures based on dual hesitant fuzzy sets and its possible applications

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Abstract

Most real-world problems are typical multi-criteria decision making problems which including ambiguity and subjectivity. Dual fuzzy sets (DHFS) are new extensions of fuzzy sets, which can cope with areas of vagueness effectively. In this paper, we propose one new similarity measure called cosine measure which has the ability to model various problems for DHFSs and study some formal relations. We provided three numerical examples including a medical diagnosis problem, an energy projects problem and a weapon selection problem to show the behaviour of the proposed cosine similarity measure.

Keywords

Cosine similarity measure Pattern recognition Multi-criteria decision making Cluster algorithm Medical diagnosis problem 

Notes

Acknowledgements

The work is supported by the National Natural Science Foundation of China (No. 61702543, 71501186), and the 333 high-level talent training project of Jiangsu Province of China (No. BRA 2016542).

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Economics and ManagementNanjing University of Science and TechnologyNanjingChina
  2. 2.Post-Doctoral Research CenterNanjing General HospitalNanjingChina
  3. 3.College of Communication EngineeringArmy Engineering University of PLANanjingChina
  4. 4.College of Command and Control EngineeringArmy Engineering University of PLANanjingChina

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