scholarly journals A novel hybrid model of ARIMA‐MCC and CKDE‐GARCH for urban short‐term traffic flow prediction

2021 ◽  
Author(s):  
Leina Zhao ◽  
Xinyu Wen ◽  
Yanpeng Wang ◽  
Yiming Shao
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction

Short-Term Traffic Flow Prediction Based on Hybrid Model

2020 ◽  
pp. 135-143
Author(s):  
Yong Hu ◽  
Meng Yu ◽  
Guanxiang Yin ◽  
Fei Du ◽  
Meng Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction

scholarly journals Short-Term Traffic Flow Prediction of Expressway: A Hybrid Method Based on Singular Spectrum Analysis Decomposition

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chunyan Shuai ◽  
Zhengyang Pan ◽  
Lun Gao ◽  
HongWu Zuo
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Spectrum Analysis ◽  
Short Term Memory ◽  
Singular Spectrum Analysis ◽  
Support Vector ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Singular Spectrum ◽  
Flow Prediction

Real-time expressway traffic flow prediction is always an important research field of intelligent transportation, which is conducive to inducing and managing traffic flow in case of congestion. According to the characteristics of the traffic flow, this paper proposes a hybrid model, SSA-LSTM-SVR, to improve forecasting accuracy of the short-term traffic flow. Singular Spectrum Analysis (SSA) decomposes the traffic flow into one principle component and three random components, and then in terms of different characteristics of these components, Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) are applied to make prediction of different components, respectively. By fusing respective forecast results, SSA-LSTM-SVR obtains the final short-term predictive value. Experiments on the traffic flows of Guizhou expressway in January 2016 show that the proposed SSA-LSTM-SVR model has lower predictive errors and a higher accuracy and fitting goodness than other baselines. This illustrates that a hybrid model for traffic flow prediction based on components decomposition is more effective than a single model, since it can capture the main regularity and random variations of traffic flow.

An adaptive hybrid model for short-term urban traffic flow prediction

2019 ◽  
Vol 527 ◽  
pp. 121065 ◽  
Author(s):  
Qinzhong Hou ◽  
Junqiang Leng ◽  
Guosheng Ma ◽  
Weiyi Liu ◽  
Yuxing Cheng
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Urban Traffic ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction
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