ArticleMethodsX2024
Some distance measures for pythagorean cubic fuzzy sets: Application selection in optimal treatment for depression and anxiety.
Article in MethodsX, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- An integrated cubic Pythagorean fuzzy MAIRCA model with novel variation coefficient similarity measure for food safety risk assessment.Scientific reports · 2026Article
- Personalized learning assessment for secondary education using a hybrid model of circular intuitionistic fuzzy and Aczel-Alsina bonferroni aggregation operator.Scientific reports · 2025Article
- Multi attribute group decision-making based on quasirung orthopair fuzzy Frank aggregation operators for optimal vehicle selection.Scientific reports · 2025Article
- Cosine similarity and distance measures forHeliyon · 2024Article
- Enhancing green supplier selection: A nonlinear programming method with TOPSIS in cubic Pythagorean fuzzy contexts.PloS one · 2024Article
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5 authors.
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Abstract
Pythagorean cubic fuzzy sets represent an advancement beyond conventional interval-valued Pythagorean sets, integrating the principles of Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets. Given the critical significance of distance measures in real-world decision-making and pattern recognition tasks, it is noteworthy that there exists a notable gap in the literature regarding distance measures specifically tailored for Pythagorean cubic fuzzy sets. The objectives of this paper are:•To define novel generalized distance measures between Pythagorean cubic fuzzy sets (PCFSs) to tackle intricate decision-making challenges.•These novel distance measures are undergoing testing on a real-world scenario concerning the management of anxiety and depression to evaluate their effectiveness and practical application.•We have illustrated the boundedness and nonlinear characteristics inherent in these distance measures. In addition, we conduct comparative analyses with existing approaches to validate the proposed methodology, thereby providing insights into its advantages and potential applications.
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