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Research Article | Open Access

Applications of picture fuzzy filters: performance evaluation of an employee using clustering algorithm

K. Tamilselvan1V. Visalakshi1Prasanalakshmi Balaji2( )
Department of Mathematics, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
Department of Computer Science, King Khalid University, Abha-62529, Saudi Arabia
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Abstract

This article defines the concepts of picture fuzzy filter, picture fuzzy grill, picture fuzzy section, picture fuzzy base, picture fuzzy subbase, picture fuzzy ultrafilter, as well as their fundamental features. Characteristics of the aforementioned concepts are addressed, and equivalence between the picture fuzzy filter and picture fuzzy grills is established. Real-world examples are offered to demonstrate the advantages of picture fuzzy filters in the classification of sets using a clustering technique. Illustration is provided to show the advantages of picture fuzzy sets and the results are compared with intuitionistic fuzzy sets. Clustering technique is applied to the picture fuzzy filter collection reduces the computational process which helps the decision makers to classify the sets with fewer iterations.

CLC number: 03E72, 54A40

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AIMS Mathematics
Pages 21069-21088

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Cite this article:
Tamilselvan K, Visalakshi V, Balaji P. Applications of picture fuzzy filters: performance evaluation of an employee using clustering algorithm. AIMS Mathematics, 2023, 8(9): 21069-21088. https://doi.org/10.3934/math.20231073

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Received: 03 May 2023
Revised: 13 June 2023
Accepted: 24 June 2023
Published: 15 September 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)