A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making

For a mathematical model to describe vague (uncertain) problems effectively, it must have the ability to explain the links between the objects and parameters in the problem in the most precise way. There is no suitable model that can handle such scenarios in the literature. This deficiency serves as...

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Main Authors: Sagvan Y. Musa, Baravan A. Asaad
Format: Article
Language:English
Published: University of New Mexico 2023-05-01
Series:Neutrosophic Sets and Systems
Subjects:
Online Access:http://fs.unm.edu/NSS/BipolarHypersoft33.pdf
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author Sagvan Y. Musa
Baravan A. Asaad
author_facet Sagvan Y. Musa
Baravan A. Asaad
author_sort Sagvan Y. Musa
collection DOAJ
description For a mathematical model to describe vague (uncertain) problems effectively, it must have the ability to explain the links between the objects and parameters in the problem in the most precise way. There is no suitable model that can handle such scenarios in the literature. This deficiency serves as motivation for this study. In this article, the bipolar hypersoft set (abbreviated, BHSS) is considered since the parameters and their opposite play a symmetrical role. We present a novel theoretical technique for solving decision-making problems using BHSS and investigate parameter reductions for these sets. Algorithms for parameter reduction are provided and explained with examples. The findings demonstrate that our suggested parameter reduction strategies remove unnecessary parameters and still retain the same decision-making options.
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spelling doaj.art-8408b7d1f083480986b8567bb96e965c2023-05-17T16:21:46ZengUniversity of New MexicoNeutrosophic Sets and Systems2331-60552331-608X2023-05-015554455610.5281/zenodo.7847778A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-MakingSagvan Y. MusaBaravan A. AsaadFor a mathematical model to describe vague (uncertain) problems effectively, it must have the ability to explain the links between the objects and parameters in the problem in the most precise way. There is no suitable model that can handle such scenarios in the literature. This deficiency serves as motivation for this study. In this article, the bipolar hypersoft set (abbreviated, BHSS) is considered since the parameters and their opposite play a symmetrical role. We present a novel theoretical technique for solving decision-making problems using BHSS and investigate parameter reductions for these sets. Algorithms for parameter reduction are provided and explained with examples. The findings demonstrate that our suggested parameter reduction strategies remove unnecessary parameters and still retain the same decision-making options.http://fs.unm.edu/NSS/BipolarHypersoft33.pdfbipolar hypersoft sethypersoft setsoft setparameter reductiondecision-making
spellingShingle Sagvan Y. Musa
Baravan A. Asaad
A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
Neutrosophic Sets and Systems
bipolar hypersoft set
hypersoft set
soft set
parameter reduction
decision-making
title A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
title_full A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
title_fullStr A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
title_full_unstemmed A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
title_short A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making
title_sort novel approach towards parameter reduction based on bipolar hypersoft set and its application to decision making
topic bipolar hypersoft set
hypersoft set
soft set
parameter reduction
decision-making
url http://fs.unm.edu/NSS/BipolarHypersoft33.pdf
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