As urbanization intensifies, the status of the traffic situation predict is becoming more and more prominent. The urban traffic flow is influenced by many factors and is characterized by strong randomness. This paper combines MSE and Adam to construct a linear LSTM to realize the prediction of short-term traffic flow based on time series. The experiment result shows that LSTM can gain the periodic features of the traffic flow. It has small error and high precision for the short-term prediction of the traffic flow based on time series, which verifies the validity of LSTM.
Application of LSTM in Short-term Traffic Flow Prediction
2020-09-01
455977 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Short-term traffic flow prediction method based on improved LSTM
Europäisches Patentamt | 2021
|Expressway Short-Term Traffic Flow Prediction Based on CNN-LSTM
Springer Verlag | 2024
|Short-term traffic flow prediction method based on Conv1D-LSTM model
Europäisches Patentamt | 2023
|Short-term traffic flow prediction method based on CASSA-LSTM algorithm
Europäisches Patentamt | 2022
|