A Novel Correlation Coefficients between Pythagorean Fuzzy Sets and Its Applications to Decision‐Making Processes

By Harish Garg. International Journal of Intelligent Systems, 2016

334 citations recorded by the source corpus.

Pythagorean fuzzy set (PFS) is one of the most successful in terms of representing comprehensively uncertain and vague information. Considering that the correlation coefficient plays an important role in statistics and engineering sciences, in this paper, after pointing out the weakness of the existing correlation coefficients between intuitionistic fuzzy sets (IFSs), we propose a novel correlation coefficient and weighted correlation coefficient formulation to measure the relationship between two PFSs. Pairs of membership, nonmembership, and hesitation degree as a vector representation with the two elements have been considered during formulation. Numerical examples of pattern recognition and medical diagnosis have been taken to demonstrate the efficiency of the proposed approach. Results computed by the proposed approach are compared with the existing indices.

Subfields: Control and Systems Engineering, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/01ec90882357b0a045d65af3a525029562fc990d

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In Control and Systems Engineering

  1. Ganeshsree Selvachandran
  2. Xindong Peng
  3. Yong Yang
  4. Suleyman Mete
  5. Huiyong Yuan

In Management Science and Operations Research

  1. Ganeshsree Selvachandran
  2. Xindong Peng
  3. Yong Yang
  4. Suleyman Mete
  5. Huiyong Yuan

In Statistics and Probability

  1. Ganeshsree Selvachandran
  2. Xindong Peng

Citations in the corpus