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.
Predicting bus ridership based on the weather conditions using deep learning algorithms.Trans- portation Research Interdisciplinary Perspectives, 19: 100833
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.