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Xinyu Hu

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Oct 2026

Local XGBoost Ensemble for Station-Level Ridership Prediction: Modeling Built Environment and Spatial Heterogeneity

A spatial proximity weighted eXtreme gradient boosting (XGBoost) ensemble to predict daily metro ridership under holidays, weekdays, and weekends is proposed, providing strong generalizability and practical value for urban transit planning and demand forecasting.

Xinyu Hu, Cong Qi, Yunpeng Zhao et al. · 0 citations

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