Analysis of the Impact of Renewable Energy, Economic, Governance, and Social Factors on National Sustainability Goals

Achieving sustainable development goals (SDGs) has been one of the greatest global challenges in recent decades. The United Nations, by setting these goals for ۲۰۳۰, places a special emphasis on environmental, economic, and social sustainability. This study aims to examine the multidimensional impacts of adopting renewable energies and other key indicators on national sustainable development goals. Statistical and machine learning approaches are used to predict the sustainable development index and assess the importance of independent variables. The results indicate that the percentage of government expenditure on health, life expectancy at birth, and primary energy consumption per capita are among the most important factors in predicting the sustainable development index. Additionally, carbon emissions, the share of renewable energies, access to electricity, and the percentage of internet usage also play significant roles. The correlation among variables shows that there are both positive and negative correlations, indicating their complex interactions on sustainable development. This research provides deep and comprehensive insights that can assist policymakers in making optimal decisions to improve sustainability.

کلیدواژه ها:

Sustainable Development Goals ، Renewable Energy ، Carbon Emissions ، Decision Tree ، Correlation ، Machine Learning