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Local soft rough approximations and their applications to conflict analysis problems

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Abstract

Local rough sets are an efficient model to analyze large-scale datasets with finite labels because they are an essential development in classical rough sets. The objective of this paper, we put forth the idea of a local soft rough approximation measure (LSRAM), which preserves rough approximation measure associated characteristics from the context of traditional rough set theory. In order to account for the uncertainty brought on by the difference between the given lower and upper approximations based on soft equivalence relation, we propose the notion of local soft knowledge distance (LSKD). Moreover, some associated proposition’s, theorems, corollaries, and a novel GM built on the LSKD model are given. Subsequently, LSRAM is combined with the suggested GM to create the enhanced LSRAM. This illustrates that the upgraded LSRAM maintains monotonicity with granularity subdivision. Further, to examine the conflict situation in the Middle East, we create a new conflict analysis model that is based on local soft rough sets in a framework of soft equivalence relations and soft indiscernible relations. Finally, we provided positive responses to a number of queries that different authors had raised. Our recently constructed model is much more effective than the existing strategies, according to an analysis of a general algorithm for conflict problems.

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Authors and Affiliations

  1. Department of Mathematics College of Science, New Campus Jazan University, Post Box 2097, Jazan, Saudi Arabia

    Moin Akhter Ansari

  2. Department of Mathematics and Statistics, Bacha Khan University, Charsadda, Khyber Pakhtunkhwa, Pakistan

    Noor Rehman

  3. Department of Mathematics and Statistics, Riphah International University, Islamabad, Pakistan

    Abbas Ali & Tahira Mubeen

  4. Department of Mathematical Engineering, Polytechnic University of Tirana, Tirana, 1001, Albania

    Kostaq Hila

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  1. Moin Akhter Ansari
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  2. Noor Rehman
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  3. Abbas Ali
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  4. Kostaq Hila
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  5. Tahira Mubeen
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Contributions

Moin Akhter Ansari was involved in the writing—review and editing, and validation. Noor Rehman contributed to the methodology, writing—review and editing, validation, and supervision. Abbas Ali performed the conceptualization, writing—original draft, and validation. Kostaq Hila assisted in writing—review and editing, validation, visualization. Tahira Mubeen contributed to writing—review and editing and validation.

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Correspondence to Noor Rehman or Kostaq Hila.

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Ansari, M.A., Rehman, N., Ali, A. et al. Local soft rough approximations and their applications to conflict analysis problems. Knowl Inf Syst (2024). https://doi.org/10.1007/s10115-024-02081-y

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