Intuitionistic fuzzy pattern recognition model in assessment of the social empowerment index for Azerbaijan - Imanov, G.; Aliyev, A. (DISCOVER ANALYTICS, 2024)
In this work, an intuitionistic fuzzy pattern recognition model is developed to evaluate the social empowerment index (SEI) for Azerbaijan. The global social and economic indices are usually computed with classical methods, in which the data uncertainty and fuzziness are not taken into account. The main advantageous points of the current research are to take into account the fuzziness of input data and incurring fuzziness along the computation process which also are the main reasons for the application of fuzzy logic extension-based tools. The presented work integrates the following operations: normalization of negative and positive affecting indicators, fuzzification of normalized data, intuitionistic fuzzy preference relation-based weight computation, checking the consistency of intuitionistic fuzzy preference relation matrices, intuitionistic fuzzy aggregation of indicators and sub-indices, and intuitionistic fuzzy pattern recognition based on similarity measures. The set-up algorithm in the proposed paper makes it a comprehensive approach in the computation of socio-economic indices, compared to the existing multiple criteria decision-making methods. The obtained results exhibit SEI level in Azerbaijan, and the proposed approach can be applied in the analysis and estimation of other socio-economic phenomena.