Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory
DOI:
https://doi.org/10.31181/dmame2104104sKeywords:
Picture fuzzy set, distance measure, rough set, indiscernible relation, students’ careerAbstract
Since the future of the society depends upon the role of students and their services construct the prosperous and advanced society, so suitable career selection for the students' is considered to be an important problem to explore. As per psychology, if a student has the required capability, and positive attitudes towards a subject in terms of interest, attitude, memory, knowledge, environment, and career, then the student will achieve more in that subject. To consider this kind of uncertain issues, picture fuzzy set and rough set are found to be appropriate due to their inherent characteristics to deal with incomplete and imprecise information. In this study, picture fuzzy set and rough set-based approaches are proposed to help the student to choose an appropriate subject and consequently provide a good service or contribution to the society particularly in that domain. The main purpose of the article is to analyse student's features in terms of career, memory, interest, knowledge, environment and attitude and then predict the appropriate stream for making the career comfortable so that the student can conveniently explore much in that area. To select students' career, a hybridized distance measure under picture fuzzy environment is proposed where the evaluating information regarding students, subjects and student's features are given in picture fuzzy numbers. In this paper, two types of hybridization approaches are proposed which are the hybridization of Hausdorff and Hamming distance measures and hybridization of Hausdorff and Euclidean distance measures. Next, we apply rough set theory to determine whether a particular subject is appropriate for a student even if there is controversy to select a stream. Lower and higher approximation with boundary region of rough set theory is used to manage inconsistency situations. Finally, two case studies are demonstrated to validate the applicability of the proposed idea.
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