A Forecasting Model for Passenger Flows of Urban Rail Transit Based on Multi-Source Spatio-Temporal Features and Optimized Ensemble Learning
In this study, we propose a novel model based on multi-source spatio-temporal features and optimized ensemble learning for forecasting station- and line-level passenger flows of urban rail transit. First, we design a spatio-temporal feature engineering method to enhance the accuracy of forecasting u...
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| Główni autorzy: | , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
MDPI AG
2026-02-01
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| Seria: | Modelling |
| Hasła przedmiotowe: | |
| Dostęp online: | https://www.mdpi.com/2673-3951/7/2/48 |
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