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Title A NOVEL STUDY OF DISTANCE BASED SIMILARITY MEASURES ON GLIVIFSESs

Author(s) Bilal Ahmed

Abstract Similarity plays an essential rule in pattern recognitions, in image processing and interdisciplinary fields such as statistics, information retrieval and data science. “Generalized linguistic interval valued intuitionistic fuzzy soft expert sets” (GLIVIFSESs) is comprehensive model in fuzzy algebra which allows flexi and more hesitant information in the form of intervals with expert expertise. We developed different types of similarity measures on GLIVIFSESs. Also separately for each similarity measure we constructed practical problems from real world data examples and checked-out the accuracy level of these measures. Behind similarity measures we attempted to apply dissimilarity measure, which plays an essential role in decision making problems. In which we firstly introduced the mathematical expression to measure dissimilarity for GLIVIFSESs and then tested the validity of that dissimilarity measure by considering the practical example related to judgments regarding the authorities of “X” state education department, and we obtained mostly accurate result. After that we used the idea of Entropy and employed it in similarity measurements which provided us comparatively most accurate results. We also introduced the concept of linguistic fuzzy implication for distance measure between GLIVIFSESs and then employed the exports opinions under linguistic fuzzy implication environment and obtained considerable accurate results.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Mathematics

Language English

Publication Date 2023-09-13

Subject Mathematics

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