The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
LSTM-based traffic flow prediction with missing data
Abstract
Abstract Traffic flow prediction plays a key role in intelligent transportation systems. However, since traffic sensors are typically manually controlled, traffic flow data with varying length, irregular sampling and missing data are difficult to exploit effectively. To overcome this problem, we propose a novel approach that is based on Long Short-Term Memory (LSTM) in this paper. In addition, the multiscale temporal smoothing is employed to infer lost data and the prediction residual is learned by our approach. We demonstrate the performance of our approach on both the Caltrans Performance Measurement System (PeMS) data set and our own traffic flow data set. According to the experimental results, our approach obtains higher accuracy in traffic flow prediction compared with other approaches.
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Cites
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Cited by
Miglani, A., & Kumar, N. (2019) · Vehicular Communications · doi:10.1016/j.vehcom.2019.100184 · Cited by 295
Congestion prediction for smart sustainable cities using IoT and machine learning approaches
Majumdar, S., Subhani, M. M., Roullier, B., Anjum, A., & Zhu, R. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102500 · Cited by 182
Short-Term Traffic Flow Prediction Based on Graph Convolutional Networks and Federated Learning
Xia, M., Jin, D., & Chen, J. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3179391 · Cited by 142
Afandizadeh, S., Abdolahi, S., & Mirzahossein, H. (2024) · Journal of Advanced Transportation · doi:10.1155/2024/9981657 · Cited by 64
Metadata
- Authors
- Tian, Y., Zhang, K., Li, J., Lin, X., & Yang, B.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 318
- Pages
- 297-305
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2889230014
- Cited by
- 544
- References
- 26
- FWCI
- 35.41
- Type
- journal article
- Language
- en
- Open access
- closed
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