Intuitionistic Fuzzy Assessment of Aggregated Quality of Life Index

Imanov, Gorkhmaz; Aliyev, A.

doi:10.1007/978-3-030-64058-3_21

Cited by 3 publications

(1 citation statement)

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“…E. Roszkowska et al evaluated Subjective Quality of Life using Intuitionistic Fuzzy Entropy-Based Weights and Intuitionistic Fuzzy Synthetic Measure [13]. In our earlier work [14] we evaluated the quality of life in Azerbaijan, where considered both argument and criteria weights. There exist numerous applications of MCDM methods for the evaluation of socio-economic indices, but the developed method in the current work is a comprehensive approach specified in the disposed algorithm.…”

Section: Introductionmentioning

confidence: 99%

Intuitionistic fuzzy pattern recognition model in assessment of the social empowerment index for Azerbaijan

Imanov,

Aliyev

2024

Preprint

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In this work, an intuitionistic fuzzy pattern recognition model is developed to evaluate the Social Empowerment Index (SEI) for Azerbaijan which is one of the four components constituting Social Quality. 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: normalisation of negative and positive affecting indicators, fuzzification of normalised 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 levels in Azerbaijan, and the proposed approach can be applied in the analysis and estimation of other socio-economic phenomena.

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Section: Introductionmentioning

confidence: 99%