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Yunpeng Wang
Researcher at Beihang University
Publications - 152
Citations - 6832
Yunpeng Wang is an academic researcher from Beihang University. The author has contributed to research in topics: Traffic flow & Vehicular ad hoc network. The author has an hindex of 31, co-authored 144 publications receiving 4499 citations. Previous affiliations of Yunpeng Wang include Chinese Ministry of Public Security.
Papers
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Journal ArticleDOI
Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.
TL;DR: Wang et al. as mentioned in this paper proposed a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy.
Posted Content
Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction
TL;DR: The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks and outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time.
Journal ArticleDOI
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.
TL;DR: Wang et al. as mentioned in this paper proposed a spatiotemporal recurrent convolutional networks (SRCNs) for traffic forecasting, which inherit the advantages of deep CNNs and LSTM neural networks.
Posted Content
Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
TL;DR: A network grid representation method that can retain the fine-scale structure of a transportation network and outperform other deep learning-based algorithms in both short-term and long-term traffic prediction is proposed.
Journal ArticleDOI
A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting
TL;DR: The forecasting accuracies of the improved KNN and of four other models are compared, and experimental results indicate that theImproved KNN model is more appropriate for short-term traffic multistep forecasting than theother models are.