Similarity Measures of Pythagorean Neutrosophic Sets with Dependent Neutrosophic Components Between T and F

Year 2020, Issue: 33, 85 - 94, 31.12.2020

Jansi Rajan Mohana Krıshnaswamy

Abstract

Clustering plays an important role in data mining, pattern recognition and machine learning. This paper proposes Pythagorean neutrosophic clustering methods based on similarity measures between Pythagorean neutrosophic sets with T and F are dependent neutrosophic components [PN-Set]. First, we define a generalized distance measure between PN-Sets and propose two distance-based similarity measures of PN-Sets. Then, we present a clustering algorithm based on the similarity measures of PN-Sets to cluster Pythagorean neutrosophic data. Finally, an illustrative example is given to demonstrate the application and effectiveness of the developed clustering methods.

Keywords

Pythagorean neutrosophic Sets with T and F are dependent neutrosophic components, clustering algorithm, distance measure, similarity measure

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