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Development and Evaluation of Recurrent Neural Network based Models for Hourly Traffic Volume and AADT Prediction
The analysis indicates that the LSTM model performs better than simple RNN and GRU models, and imputation performs better than masking to predict future traffic volume.
Development of Statewide AADT Estimation Model from Short-Term Counts: A Comparative Study for South Carolina
SVR models are validated for each roadway functional class using the 2016 ATR data and selected short-term count data collected by the South Carolina Department of Transportation (SCDOT).
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