Hamming distance

Mathematics

Boundary (topology)

Rough set

Algorithm

Image (mathematics)

Similarity (geometry)

Data mining

Set theory

Library science

Mathematical analysis

Artificial intelligence

Set (abstract data type)

Programming language

Measure (data warehouse)

Subject (documents)

Computer science

Fuzzy set

Fuzzy logic

Selection (genetic algorithm)

Decision Making Applications in Management and Engineering

Since the future of the society depends upon the role of students, so suitable career selection methods for the students are considered to be an important problem to explore. It is assumed that if a student has the required capability and positive attitudes towards a subject, then the student will achieve more in that subject. To consider the uncertain issues involved with students’ career selection, picture fuzzy set (PFS) and rough set based approaches are proposed in this study as they are found to be appropriate due to their inherent characteristics to deal with incomplete and imprecise information. For the purpose of selecting a suitable career, the article analyzes student's features in terms of career, memory, interest, knowledge, environment and attitude. We propose two hybridized distance measures using Hausdorff, Hamming and Euclidian distances under picture fuzzy environment where the evaluating information regarding students, subjects and student's features are given in picture fuzzy numbers. Then we present an algorithmic approach using the proposed distance measures and rough set theory. We apply rough set theory to determine whether a particular subject is suitable 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 the inconsistent situations. Finally, two case studies are demonstrated to validate the applicability of the proposed idea.

Career selection of students using hybridized distance measure based on picture fuzzy set and rough set theory