AI for Sustainability: A Smart Data Model to Guide Governmental Decisions
This paper proposes a smart data analytics framework utilizing machine learning models (Linear Regression, Random Forest, and XGBoost) to evaluate and predict sustainability indicators aligned with UN SDGs, demonstrating that XGBoost offers the most stable performance while providing governments with an interpretable, evidence-based tool for optimizing resource allocation and long-term strategic planning.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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