#3747. Parameter reduction analysis under interval-valued m-polar fuzzy soft information

October 2026publication date
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Journal’s subject area:
Artificial Intelligence;
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Abstract:
This paper formalizes a novel model that is able to use both interval representations, parameterizations, partial memberships and multi-polarity. These are differing modalities of uncertain knowledge that are supported by many models in the literature. An enhanced combination of interval-valued m-polar fuzzy (IVmF) sets and soft sets produces this model. An algorithm is developed to solve decision-making problems having data in interval-valued m-polar fuzzy soft form. It is applied to two numerical examples. They are respectively called parameter reduction based on optimal choice, rank based parameter reduction, and normal parameter reduction. Two real case studies for the selection of best site for an airport construction are studied.
Keywords:
Algorithm; Decision-making; Parameter reduction; Soft set

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