Abstract
Based on the time sequence of the online car-hailing data and the change trend characteristics of the online car-hailing data, the short-term prediction of the demand for online car-hailing is carried out. Established the short-term prediction model of the online car-hailing demand, which is based on ARIMA, single feature LSTM and multi feature LSTM respectively. The optimal parameters and structure of the model are determined by using the actual demand data of drip-drip taxi platform, and the comparative experiments are carried out. The experimental results show that the multi feature LSTM model is the best.
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