An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities

Abstract We introduce a novel extension of conventional fuzzy sets in this paper: called trimorphic fuzzy sets. As per our research, trimorphic fuzzy sets which exhibit greater capability than intuitionistic fuzzy sets, picture fuzzy sets and bipolar fuzzy sets, present a viable approach to address...

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Bibliographic Details
Main Authors: Minhaj, Muneeza, Asghar Khan, Mohammad Khishe, Abdu H. Gumaei, Samah M. Alzanin, Bader Fahad Alkhamees, Shahzaib Ashraf
Format: Article
Language:English
Published: Springer 2025-04-01
Series:International Journal of Computational Intelligence Systems
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Online Access:https://doi.org/10.1007/s44196-025-00770-2
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Summary:Abstract We introduce a novel extension of conventional fuzzy sets in this paper: called trimorphic fuzzy sets. As per our research, trimorphic fuzzy sets which exhibit greater capability than intuitionistic fuzzy sets, picture fuzzy sets and bipolar fuzzy sets, present a viable approach to address ambiguity and uncertainty in decision-making scenarios. We present a complete characterization of trimorphic fuzzy sets, discuss their properties, and consider applications to real-world decision-making scenarios. We also present a case study to further highlight the practical applications of trimorphic fuzzy sets. We look into a few aggregation strategies for trimorphic fuzzy data in this work. We create the MCDM method using trimorphic fuzzy aggregation operators to help people with disabilities choose AI-Powered Assistive Technologies. We have also presented the extended TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method with trimorphic fuzzy numbers. A numerical example for selection of AI-Powered Assistive Technologies using TOPSIS method is also provided.
ISSN:1875-6883