Hypersoft sets on nearness approximation space and its topology

Abstract

Hypersoft set theory represents an advanced version to soft set theory, offering enhanced capabilities for addressing uncertainty. By combining hypersoft set theory with nearness approximation spaces, a novel mathematical model known as near hypersoft set emerges. This hybrid model enables improved decision-making accuracy. In this study, our focus is on selecting an object from a product containing a function parameter set described by a distinct Cartesian feature with multiple arguments. Furthermore, we define fundamental features and topology on this set.