Intuitionistic fuzzy dynamic pattern recognition model for evaluation of Climate-Economic Interaction Index (CEII) for Azerbaijan

LA EMPRESA DE FUTURO Y SU CONTRIBUCIÓN AL DESARROLLO, vol.0, no.0, pp.2115-2126, 2024 (Peer-Reviewed Journal)

This paper introduces the Intuitionistic Fuzzy Dynamic Pattern Recognition (IFDPR) model for the

evaluation of the Climate-Economic Interaction Index (CEII) in Azerbaijan. Given the increasing unpredictability

and complex interdependencies between climatic conditions and economic performance, traditional models often fall

short in accurately capturing the full spectrum of climate-economic interactions. The IFDPR model addresses these

shortcomings by applying intuitionistic fuzzy logic, which effectively manages the ambiguity inherent in climatic

and economic data. This approach not only enhances the robustness of the analysis but also improves the precision in

the evaluation of how climate-related changes impact economic activities.

We outline a comprehensive methodology for integrating the IFDPR model into the CEII computation, emphasizing

its relevance in processing and interpreting fluctuating data across a set of economic indicators from 2015 to 2023.

Our proposed model systematically assesses and weights various economic indicators such as energy consumption,

labor productivity, and greenhouse gas emissions, reflecting their dynamic influence on the economy's susceptibility

to climate change. The resulting analysis not only provides a nuanced understanding of the economic impacts

through the CEII but also aligns with strategic policy-making by offering refined data that can guide economic

resilience and sustainability efforts. Our findings reveal a nuanced trajectory of the CEII over the observed period,

suggesting implications for both economic planning and environmental strategy formulation in Azerbaijan.