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What is Sustainability 12 01481 about?

This study evaluates five machine learning models to predict life cycle global warming and eutrophication impacts from corn production in the Midwest U.S. The gradient boosting regression tree model demonstrated the highest predictive accuracy for both global warming and eutrophication impacts, significantly outperforming traditional process-based models in efficiency. The findings suggest that machine learning can effectively estimate spatially explicit life cycle environmental impacts, providing a valuabl

Author

kelris.1.prspbpdh

Language

EN