Localized polygon-based models trained on clustered bus stops achieve prediction accuracy comparable to a single global model when using ridership, spatial, weather, and temporal features.
A matheuristic for transfer synchronization through integrated timetabling and vehi- cle scheduling.Transportation Research Part B: Method- ological, 109:128–149
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Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction
Localized polygon-based models trained on clustered bus stops achieve prediction accuracy comparable to a single global model when using ridership, spatial, weather, and temporal features.