A decision-tree-rule feature augmentation is reported to improve neural network travel demand forecasts, but the evaluation is in-sample and lacks error bars.
Gravity model in the korean highway,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
REJECT 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Neurosymbolic AI for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks
A decision-tree-rule feature augmentation is reported to improve neural network travel demand forecasts, but the evaluation is in-sample and lacks error bars.