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Parametric Directed Divergence Measure for Pythagorean Fuzzy Set and Their Applications to Multi-criteria Decision-Making

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Pythagorean Fuzzy Sets

Abstract

PFS (Pythagorean Fuzzy Set), extension of IFS (Intuitionistic Fuzzy Set), is basically more capable in uncertain, vague, or imprecise situation. That’s why it is being broadly applied in various realistic problems like pattern recognition, medical diagnosis, etc. On account of this point, a new generalized parametric divergence measure of order \( \alpha \) and degree \( \beta \) under the environment of PFSs has been investigated in this work. Some desirable properties of this measure are also being studied. Additionally, an algorithm based on the measure under PFSs is provided along with an illustration of decision-making problem.

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Authors and Affiliations

  1. JSS Academy of Technical Education, Noida, Uttar Pradesh, India

    Nikunj Agarwal

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  1. Nikunj Agarwal
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Correspondence to Nikunj Agarwal .

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Editors and Affiliations

  1. School of Mathematics, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India

    Harish Garg

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Agarwal, N. (2021). Parametric Directed Divergence Measure for Pythagorean Fuzzy Set and Their Applications to Multi-criteria Decision-Making. In: Garg, H. (eds) Pythagorean Fuzzy Sets. Springer, Singapore. https://doi.org/10.1007/978-981-16-1989-2_3

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