Fuzzy Pattern Recognition Model for Simulating the Green Growth Index for Azerbaijan

This paper presents a fuzzy pattern recognition model (FPRM), proposed to evaluate, and simulate potential improvements of Green Growth Index (GGI) for Azerbaijan that is one of the main targets of Sustainable Development Goals. Global Green Growth Institute (GGGI) practices the geometrical average method as a general rule for computation of GGI. The FPRM accommodates the inherent uncertainty and fuzziness in GGI indicators by employing fuzzy logic techniques, thereby enhancing the accuracy and robustness of GGI evaluation and simulation. The proposed approach advances the works in the current research course with the developed algorithm and model for fuzzy pattern recognition process. Computational results showcase the effectiveness of the FPRM in evaluating GGI levels for Azerbaijan and simulating the potential impacts of interventions on GGI indicators. The study contributes to advancing green growth research and facilitates evidence-based policymaking towards sustainable development by providing a structured methodology for GGI assessment and improvement.