Prioritizing disability support systems by using Tamir's complex fuzzy Dombi aggregation operators.

Fuzzy sets can model the inherent ambiguity and subjectivity in disability assessment by allowing for flexible classification and decision-making. This contributes to the development of flexible clinical support systems that are effective in meeting individual needs. Subjective assessments of an individual's needs and talents are common in disability. Conventional clear-cut methodologies classify people as "disabled" or "not disabled," which may not fully reflect the wide range of disabilities. Fuzzy sets allow for degrees of membership, such as (a) Person A has 70% mobility impairment. (b) Person B needs 50% personal care support. This method takes into account the subjectivity and variability of disability assessments. Designing adaptive systems for people with disabilities requires the use of fuzzy sets for clinical support. For this purpose, we have proposed the theory of aggregation operators based on a complex fuzzy set. Aggregation operators help us to convert overall information to a single value that can help our clinical support system. Moreover, for the application of the delivered approach, we have proposed an algorithm and utilized this approach for the selection of the best disability support system. We have provided a comparative analysis of the defined theory to discuss the advantages of the initiated work.