Open Access

ARTICLE

On Multi-Granulation Rough Sets with Its Applications

Radwan Abu-Gdairi¹, R. Mareay^2,*, M. Badr³

1 Department of Mathematics, Faculty of Science, Zarqa University, Zarqa, 13132, Jordan
2 Department of Mathematics, Faculty of Science, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt
3 Department of Mathematics, Faculty of Science, New Valley University, El Kharga, 72713, Egypt

* Corresponding Author: R. Mareay. Email:

(This article belongs to the Special Issue: Emerging Trends in Fuzzy Logic)

Computers, Materials & Continua 2024, 79(1), 1025-1038. https://doi.org/10.32604/cmc.2024.048647

Received 14 December 2023; Accepted 29 February 2024; Issue published 25 April 2024

Abstract

Recently, much interest has been given to multi-granulation rough sets (MGRS), and various types of MGRS models have been developed from different viewpoints. In this paper, we introduce two techniques for the classification of MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novel approximation space is established by leveraging the underlying topological structure. The characteristics of the newly proposed approximation space are discussed. We introduce an algorithm for the reduction of multi-relations. Secondly, a new approach for the classification of MGRS based on neighborhood concepts is introduced. Finally, a real-life application from medical records is introduced via our approach to the classification of MGRS.

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Keywords

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