Construction of New Similarity Measures for Complex Pythagorean Fuzzy Sets and Their Applications in Decision-Making Problems

Authors

  • Donglai Wang College of Computer Science, Chongqing University, Chongqing 400044, China. https://orcid.org/0009-0009-3320-0045 Author
  • Sukumar Letchmunan School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia. https://orcid.org/0000-0002-3521-7141 Author
  • Juan Liao School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia. https://orcid.org/0000-0003-3935-0457 Author
  • Haoye Qiu School of Computer Science and Engineering, Southeast University, Nanjing 211189, China. https://orcid.org/0000-0001-6056-2070 Author
  • Zhe Liu School of Computer Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia. https://orcid.org/0000-0002-8580-9655 Author

DOI:

https://doi.org/10.59543/jidmis.v2i.11737

Keywords:

Complex Pythagorean fuzzy sets, similarity measures, trigonometric function, decision-making

Abstract

Complex Pythagorean fuzzy sets (CPFSs) extend Pythagorean fuzzy sets by expressing membership, non-membership, and hesitancy degrees using complex numbers. An urgent issue in CPFSs is determining how to accurately measure the similarity between sets. Similarity measures are crucial for assessing the closeness between two objects and are extensively applied in decision-making. In this paper, we propose new similarity measures based on trigonometric functions and their weighted representations. Additionally, we investigate the properties these measures satisfy and demonstrate their effectiveness through several numerical examples. Lastly, we apply these similarity measures to decision-making problems, including pattern recognition and medical diagnosis.

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Published

2025-01-03

How to Cite

Donglai Wang, Sukumar Letchmunan, Juan Liao, Haoye Qiu, & Zhe Liu. (2025). Construction of New Similarity Measures for Complex Pythagorean Fuzzy Sets and Their Applications in Decision-Making Problems. Journal of Intelligent Decision Making and Information Science, 2, 156–173. https://doi.org/10.59543/jidmis.v2i.11737

Issue

Vol. 2 (2025)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

JIDMIS is published Open Access under a Creative Commons CC-BY 4.0 license. Authors retain full copyright, with the first publication right granted to the journal.