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April 1, 2026International Journal of Fuzzy Logic and Intelligent Systems0 citationsOpen Access

Enhancing Economic Decision-Making through the Application of Alpha Basic-Rough Sets

MEMostafa A. El-GayarNMNaglaa M. MadboulyANAshraf S. Nawar

Key Points

  • The aim is to enhance economic decision-making using a new class of generalized rough sets called b-approximations.
  • Developed a new framework based on b-approximations from basic neighborhood systems.
  • Defined five operators and analyzed their performance through proofs and examples.
  • Conducted economic experiments to evaluate classification accuracy of high-growth countries.
  • Validating findings through MATLAB implementation for computational efficiency.
  • Achieved up to 100% classification accuracy in identifying high-growth countries.
  • Demonstrated superior accuracy compared to traditional approaches.
  • Validated computational efficiency using a MATLAB implementation.

Abstract

This study introduces b -approximations, a new class of generalized rough sets derived from basic neighborhood systems.Unlike traditional approaches that require strict topological assumptions, this framework preserves Pawlak's principles while offering greater simplicity and applicability.Five operators were defined and analyzed, with proofs and examples confirming their superior accuracy.Economic experiments demonstrate up to 100% classification accuracy in identifying high-growth countries, whereas a MATLAB implementation validates the computational efficiency.Overall, the proposed approach provides a flexible and practical tool for precise decision-making with broad application potential.

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Cite This Study

El-Gayar et al. (2026) studied this question.

synapsesocial.com/papers/69cd79e15652765b073a6ab8https://doi.org/10.5391/ijfis.2026.26.1.98
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