A Study on Soft Multi-Granulation Rough Sets and Their Applications

Rough set (RS) and soft set (SS) theories are two successful mathematical approaches to dealing with uncertainty in data analysis. The classical soft rough set (SRS) theory proposed by Feng et al. (2011) offers a formal theoretical framework for solving the uncertainty under a single granulation env...

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Main Authors: Saba Ayub, Waqas Mahmood, Muhammad Shabir, Ali N. A. Koam, Rizwan Gul
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9934891/
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author Saba Ayub
Waqas Mahmood
Muhammad Shabir
Ali N. A. Koam
Rizwan Gul
author_facet Saba Ayub
Waqas Mahmood
Muhammad Shabir
Ali N. A. Koam
Rizwan Gul
author_sort Saba Ayub
collection DOAJ
description Rough set (RS) and soft set (SS) theories are two successful mathematical approaches to dealing with uncertainty in data analysis. The classical soft rough set (SRS) theory proposed by Feng et al. (2011) offers a formal theoretical framework for solving the uncertainty under a single granulation environment. However, it is essential to note that the SRS theory cannot be applied in the context of multi-granulation in the real world. To address this issue, in this paper, we introduce the idea of soft multi-granulation RS (SMGRS) model based on two soft binary relations (S-BRs). Axiomatic operations, lower soft rough approximation space (lower SRA-space) and upper soft rough approximation space (upper SRA-space), are defined through after sets of soft relations. After that, the concept of SMGRSs is applied to a significant part of commutative algebra, group theory. In this respect, the primitive notions of SRA-spaces are defined with the help of two normal soft groups (NSGs). In groups, several important structural properties related to SMGRS are investigated in detail with illustrative examples. It is shown that SMGRS in groups may be influential in decision-making (DM) by some numerical examples. To demonstrate the flexibility, superiority, and effectiveness of the suggested technique, some comparative examples are given with some existing methods.
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spelling doaj.art-94b3e1f0ecc24f41bbd8e7a1e5fcce8c2022-12-22T04:38:06ZengIEEEIEEE Access2169-35362022-01-011011554111555410.1109/ACCESS.2022.32186959934891A Study on Soft Multi-Granulation Rough Sets and Their ApplicationsSaba Ayub0https://orcid.org/0000-0002-6963-3127Waqas Mahmood1https://orcid.org/0000-0003-1171-8782Muhammad Shabir2Ali N. A. Koam3https://orcid.org/0000-0002-5047-9908Rizwan Gul4https://orcid.org/0000-0002-6139-1872Department of Mathematics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Mathematics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Mathematics, Quaid-i-Azam University, Islamabad, PakistanDepartment of Mathematics, College of Science, Jazan University, Jazan, Saudi ArabiaDepartment of Mathematics, Quaid-i-Azam University, Islamabad, PakistanRough set (RS) and soft set (SS) theories are two successful mathematical approaches to dealing with uncertainty in data analysis. The classical soft rough set (SRS) theory proposed by Feng et al. (2011) offers a formal theoretical framework for solving the uncertainty under a single granulation environment. However, it is essential to note that the SRS theory cannot be applied in the context of multi-granulation in the real world. To address this issue, in this paper, we introduce the idea of soft multi-granulation RS (SMGRS) model based on two soft binary relations (S-BRs). Axiomatic operations, lower soft rough approximation space (lower SRA-space) and upper soft rough approximation space (upper SRA-space), are defined through after sets of soft relations. After that, the concept of SMGRSs is applied to a significant part of commutative algebra, group theory. In this respect, the primitive notions of SRA-spaces are defined with the help of two normal soft groups (NSGs). In groups, several important structural properties related to SMGRS are investigated in detail with illustrative examples. It is shown that SMGRS in groups may be influential in decision-making (DM) by some numerical examples. To demonstrate the flexibility, superiority, and effectiveness of the suggested technique, some comparative examples are given with some existing methods.https://ieeexplore.ieee.org/document/9934891/Multi-granulation rough setssoft setssoft binary relationsnormal soft groupsdecision-making
spellingShingle Saba Ayub
Waqas Mahmood
Muhammad Shabir
Ali N. A. Koam
Rizwan Gul
A Study on Soft Multi-Granulation Rough Sets and Their Applications
IEEE Access
Multi-granulation rough sets
soft sets
soft binary relations
normal soft groups
decision-making
title A Study on Soft Multi-Granulation Rough Sets and Their Applications
title_full A Study on Soft Multi-Granulation Rough Sets and Their Applications
title_fullStr A Study on Soft Multi-Granulation Rough Sets and Their Applications
title_full_unstemmed A Study on Soft Multi-Granulation Rough Sets and Their Applications
title_short A Study on Soft Multi-Granulation Rough Sets and Their Applications
title_sort study on soft multi granulation rough sets and their applications
topic Multi-granulation rough sets
soft sets
soft binary relations
normal soft groups
decision-making
url https://ieeexplore.ieee.org/document/9934891/
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