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

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.