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Random forest advances boost explainability in ecological modeling

Researchers have shown how random forest algorithms can be applied to complex ecological models to uncover the mechanisms driving system behavior. By analyzing a stage‑structured consumer‑resource ...

Machine learning tool pinpoints optimal locations for tree planting, offering a powerful tool for climate mitigation

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...
IEEE

Research on Multi-Dimensional Prediction Methods Based on Random Forest and Xgboost Algorithms

Abstract: This study established a multi-dimensional prediction framework centred on random forest and XGBoost. Firstly, baseline prediction values are generated using a theoretical model, combined ...
IEEE

Estimating Accident Clearance Time: A Comparative Study of Genetic Algorithm-Optimized Neural Network and Random Forest Approaches

Abstract: This study applies artificial intelligence (AI) techniques to develop and evaluate predictive models for road accident clearance time - an essential element in traffic management and public ...