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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| Format: | Article |
| Language: | English |
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Springer
2025-04-01
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| 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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| author | Minhaj Muneeza Asghar Khan Mohammad Khishe Abdu H. Gumaei Samah M. Alzanin Bader Fahad Alkhamees Shahzaib Ashraf |
| author_facet | Minhaj Muneeza Asghar Khan Mohammad Khishe Abdu H. Gumaei Samah M. Alzanin Bader Fahad Alkhamees Shahzaib Ashraf |
| author_sort | Minhaj |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-08de057819ea4ec4b51a06d9f77fa436 |
| institution | DOAJ |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-08de057819ea4ec4b51a06d9f77fa4362025-08-20T03:06:50ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-04-0118112810.1007/s44196-025-00770-2An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with DisabilitiesMinhaj0Muneeza1Asghar Khan2Mohammad Khishe3Abdu H. Gumaei4Samah M. Alzanin5Bader Fahad Alkhamees6Shahzaib Ashraf7Department of Mathematics, Abdul Wali Khan UniversityDepartment of Mathematics, Abdul Wali Khan UniversityDepartment of Mathematics, Abdul Wali Khan UniversityDepartment of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical SciencesDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz UniversityDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz UniversityDepartment of Information Systems, College of Computer and Information Sciences, King Saud UniversityInstitute of Mathematics, Khwaja Fareed University of Engineering and Information TechnologyAbstract 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.https://doi.org/10.1007/s44196-025-00770-2Fuzzy setTrimorphic fuzzy setsDecision-makingAggregation operatorsDisabilitiesAssistive technologies |
| spellingShingle | Minhaj Muneeza Asghar Khan Mohammad Khishe Abdu H. Gumaei Samah M. Alzanin Bader Fahad Alkhamees Shahzaib Ashraf An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities International Journal of Computational Intelligence Systems Fuzzy set Trimorphic fuzzy sets Decision-making Aggregation operators Disabilities Assistive technologies |
| title | An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities |
| title_full | An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities |
| title_fullStr | An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities |
| title_full_unstemmed | An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities |
| title_short | An Intelligent Decision Support System for Selecting Optimal AI-Powered Assistive Technology for Individuals with Disabilities |
| title_sort | intelligent decision support system for selecting optimal ai powered assistive technology for individuals with disabilities |
| topic | Fuzzy set Trimorphic fuzzy sets Decision-making Aggregation operators Disabilities Assistive technologies |
| url | https://doi.org/10.1007/s44196-025-00770-2 |
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