A Flow Feedback Traffic Prediction Based on Visual Quantified Features
Author:
Affiliation:
1. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China
2. College of Economics and Management, China Jiliang University, Hangzhou, China
3. Institute of Engineering Innovation, Changsha, China
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Provincial Universities of Zhejiang
China State Construction Engineering Corporation Fifth Bureau (CSCEC5B) Key Research Project
National Science Foundation of Zhejiang Province, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10235283/10122471.pdf?arnumber=10122471
Reference30 articles.
1. Does LSTM outperform 4DDTW-KNN in lane change identification based on eye gaze data?
2. Robust Least Squares Twin Support Vector Regression With Adaptive FOA and PSO for Short-Term Traffic Flow Prediction
3. Global-Local Temporal Convolutional Network for Traffic Flow Prediction
4. Capturing Car-Following Behaviors by Deep Learning
5. Streets: A novel camera network dataset for traffic flow;snyder;Proc Adv Neural Inf Process Syst,2019
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