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AIMS Mathematics

2020, Volume 5, Issue 2: 1050-1061. doi: 10.3934/math.2020073
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Research article

A novel entropy measure of Pythagorean fuzzy soft sets

  • 1.
    Department of Mathematics, National Institute of Technology Calicut-673 601, India
  • 2.
    School of Mathematics, Thapar Institute of Engineering & Technology, Deemed University Patiala, Punjab, India
  • Received: 16 October 2019 Accepted: 19 December 2019 Published: 10 January 2020

  • MSC : 03E72, 62A86, 68T35, 90B50

  • Pythagorean fuzzy soft set (PFSS) is one of the useful extension of the Pythagorean fuzzy set (PFS) to deal with the vagueness and uncertainties in the data. The major advantages of PFSS over the other existing sets are to consider the parameterized tool of the family of PFS. Keeping this advantage, in this paper we define some new entropy measures for PFSS to compute the degree of fuzziness of the set. The axiomatic definition and their validity are stated. The larger the entropy, the lesser the vagueness and so, the decision making based on entropy is a useful one. Further, a decisionmaking algorithm is explored to solve the decision-making problem under the PFSS environment. A numerical example is given to validate the method and compare their performance with the existing intuitionistic fuzzy soft set entropy measures.

    Citation: T. M. Athira, Sunil Jacob John, Harish Garg. A novel entropy measure of Pythagorean fuzzy soft sets[J]. AIMS Mathematics, 2020, 5(2): 1050-1061. doi: 10.3934/math.2020073

    Related Papers:

  • Pythagorean fuzzy soft set (PFSS) is one of the useful extension of the Pythagorean fuzzy set (PFS) to deal with the vagueness and uncertainties in the data. The major advantages of PFSS over the other existing sets are to consider the parameterized tool of the family of PFS. Keeping this advantage, in this paper we define some new entropy measures for PFSS to compute the degree of fuzziness of the set. The axiomatic definition and their validity are stated. The larger the entropy, the lesser the vagueness and so, the decision making based on entropy is a useful one. Further, a decisionmaking algorithm is explored to solve the decision-making problem under the PFSS environment. A numerical example is given to validate the method and compare their performance with the existing intuitionistic fuzzy soft set entropy measures.


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  • © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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