Integrating Data Mining and System Dynamics for Enhanced Model Energy Policy Development and Sustainability Assessment

A powerful approach has emerged in the form of integrating data mining techniques with the system dynamics method to inform evidence-based policy decisions. This article delves into the utilization of data mining in the development of energy policies, synergizing it with system dynamics to elevate energy sustainability and efficiency. The exploration includes assessing the carrying capacities of dynamic systems, evaluating the robustness of the 'Plan for the Future' reference scenario in dynamic settings, and extracting novel socio-economic parameters using advanced data mining techniques. Sensitivity analysis of a fully dynamic model identifies critical parameters for system stability, while an energy-economy model is constructed. The article introduces dynamic machine algorithms designed for decision-making systems, leveraging data science to unveil the ultimate capacity of the energy policy model. This encompasses multiple indices, such as the Index of Economic Freedom, Export Quality Index, Energy Security Risk, Iran's foreign direct investment, Sustainable Development Index, Country & Product Complexity Index, International Cooperation, Iran's credit rating in international trade, Trade (% of GDP), Export Diversification Index, Economic Resilience Index, Global Conflict Risk Index, Oil Revenue Reliance (% of GDP), and ensures energy security projections up to ۲۰۷۰. Furthermore, it assesses dynamic subnet connection point variables, including international bargaining power and the acceptability index of international participation in terms of their impact polarity, facilitating future research endeavors.

کلیدواژه ها:

Transformation ، Sustainability ، Data mining ، Occurrence scenario power ، system dynamics