The study demonstrates a novel decision-making approach using Bipolar T-Spherical Fuzzy Hypersoft Set, indicating improved selection of air filters based on multiple attributes.
Key Points
Bipolar T-Spherical Fuzzy Hypersoft Set theory provides a robust framework for decision-making involving multiple attributes.
The application of this methodology shows a notable improvement in choosing the best air filter for reducing industrial air pollution.
Fundamental algebraic properties of Bipolar T-Spherical Fuzzy Hypersoft Sets are established to support this decision-making process.
Utilizing a Multi-Attribute Decision-Making approach allows for a comprehensive comparison of various air filters.