Bipolar fuzzy dominance rough WASPAS approach for AI-based radar evaluation

Muhammad  Iftikhar; Ubaid Ur  Rehman; Tahir  Mahmood

doi:10.59400/adecp4022

Bipolar fuzzy dominance rough WASPAS approach for AI-based radar evaluation

Muhammad Iftikhar
Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad 44000, Pakistan
Ubaid Ur Rehman
Department of Mathematics, University of Management and Technology, Lahore 54700, Pakistan
Tahir Mahmood
Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad 44000, Pakistan

Article ID: 4022

Keywords: artificial intelligence; radar system; multi-criteria decision making (MCDM); bipolar fuzzy dominance rough set approach

Abstract

The selection of an AI-based radar system to detect drones is a multi-criteria decision-making (MCDM) problem with many conflicting criteria. Exchanges between positive and negative aspects of each radar system in uncertain and incomplete information should be assessed by decision-makers. The traditional MCDM models are usually not effective in dealing with such complexities, especially when both positive and negative aspects are involved, and comparative reasoning is needed (dominance). In order to address these shortcomings, this article suggests an advanced model using the bipolar fuzzy dominance rough set (BFDRS) approach. The suggested method combines fuzzy logic to deal with uncertainty, dominance-based rough sets to model preferences, and bipolar fuzzy sets to manage dual-natured assessments. In order to operationalize the framework, we propose two new aggregation operators, namely bipolar fuzzy dominance rough dombi averaging (BFDRDA) and bipolar fuzzy dominance rough dombi geometric (BFDRDG), to combine expert opinions in the context of multiple criteria successfully. After that, we develop an MCDM methodology, which is the WASPAS method, within the framework of BFDRS, to prioritize AI radar alternatives in the presence of uncertainty. An extensive case study proves the relevance of the suggested model, and a comparative analysis with the currently existing ones proves its strength and higher decision-support abilities in complex and contradictory environments.

Published

2026-05-29

How to Cite

Iftikhar, M., Rehman, U. U., & Mahmood, T. (2026). Bipolar fuzzy dominance rough WASPAS approach for AI-based radar evaluation. Advances in Differential Equations and Control Processes, 33(2). https://doi.org/10.59400/adecp4022

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Vol. 33 No. 2 (2026): In Progress

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Article

This work is licensed under a Creative Commons Attribution 4.0 International License.

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