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Yanjie Duan
Researcher at Chinese Academy of Sciences
Publications - 12
Citations - 3450
Yanjie Duan is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Deep learning & Traffic flow. The author has an hindex of 9, co-authored 12 publications receiving 2513 citations. Previous affiliations of Yanjie Duan include Huawei.
Papers
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Journal ArticleDOI
Traffic Flow Prediction With Big Data: A Deep Learning Approach
TL;DR: A novel deep-learning-based traffic flow prediction method is proposed, which considers the spatial and temporal correlations inherently and is applied for the first time that a deep architecture model is applied using autoencoders as building blocks to represent traffic flow features for prediction.
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Generative adversarial networks: introduction and outlook
TL;DR: It is concluded that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration, and can provide substantial algorithmic support for parallel intelligence.
Proceedings ArticleDOI
Travel time prediction with LSTM neural network
TL;DR: A deep learning model, the LSTM neural network model, is explored for travel time prediction by employing the travel time data provided by Highways England and obtains the optimal structure within the setting range for each link.
Journal ArticleDOI
An efficient realization of deep learning for traffic data imputation
TL;DR: This work developed an algorithm for efficient realization of deep learning for traffic data imputation by training the model hierarchically using the full set of data from all vehicle detector stations, and investigated why the deep leaning model works well for traffic Data Imputation by visualizing the features extracted by the first hidden layer.
Journal ArticleDOI
Social media based transportation research: the state of the work and the networking
TL;DR: This paper reviews social media based transportation research with social network analysis methods, and summarizes main research topics in this field, and reports collaboration patterns at levels of researchers, institutions, and countries.