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Intuitionistic Fuzzy Index Matrices in Linear Regression Analysis
Velichka Traneva and Stoyan Tranev
In this work, the coefficients of the simple linear regression model between the study variables in an intuitionistic fuzzy (IF) environment are found using an index matrix approach (IFIM-LRA). In order to store and analyze a sizable IF dataset, we suggest extending the linear classical least squares approach with the use of intuitionistic fuzzy sets (IFSs) and index matrices (IMs). Furthermore, an approach is proposed to assess the applicability of the model in an IF environment. The use of conventional regression analysis and the IFIM–LRA technique to model the operational revenue of the Hospital for Active Treatment, Bulgaria is examined using an actual data set with investment cost values for the years 2017–2022. The document’s originality comes from the usage of the defined IFIM-LRA and how it was applied to the examined hospital investment expenses and income for 2017–2022.
Keywords: Index matrices, intuitionistic fuzzy logic, regression analysis