SDLSTM-ARIMA hybrid model claims higher accuracy than standalone ARIMA or AR for traffic flow by incorporating time singularity ratios in LSTM dropout for unequal-interval combinations.
(2016) ‘Short-term traffic flow rate forecasting based on identifying similar traffic patterns ’, Transportation Research Part C: Emerging Technologies, Vol
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Traffic Flow Combination Forecasting Method Based on Improved LSTM and ARIMA
SDLSTM-ARIMA hybrid model claims higher accuracy than standalone ARIMA or AR for traffic flow by incorporating time singularity ratios in LSTM dropout for unequal-interval combinations.