Interval-Valued Neutrosophic Rough Soft Set Based Intelligent Decision-Making Framework for Water Quality Assessment

Resumen

This study introduces a novel framework, Interval-Valued Neutrosophic Rough Soft Sets (IVNRSSs), designed to improve handling uncertainty, imprecision, and vagueness in complex decision-making scenarios. By integrating soft, rough, and interval-valued neutrosophic set theories, the framework offers a robust methodology for addressing indeterminacy and incomplete data. The theoretical foundation of IVNRSSs is built upon fundamental operations, including intersection, union, complement, and novel aggregation union operators tailored for multi-criteria decision-making (MCDM) applications. The practical applicability of the framework is demonstrated through a water quality assessment, where it successfully classifies river segments based on key water quality parameters such as pH, Dissolved Oxygen (DO), and Biochemical Oxygen Demand (BOD). The study results show that the pollution scores for the river segments were computed, classifying the segments such as "Good," "Moderate," and "Poor," with corresponding pollution levels. These findings highlight the framework's ability to manage incomplete and inconsistent data, providing a reliable and comprehensive water quality evaluation. Compared to traditional models, the IVNRSS approach offers enhanced flexibility, stability, and adaptability. This study not only contributes to the theoretical development of neutrosophic, soft, and rough set theories but also establishes IVNRSSs as a powerful tool for water quality decision-making. Future research will explore further advancements in the application and computational efficiency of this framework.