The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Dynamic prediction of traffic volume through Kalman filtering theory
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Citations
Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Cited by
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
Zhao, L., Song, Y., Zhang, C., Liu, Y., Wang, P., Lin, T., Deng, M., & Li, H. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2935152 · Cited by 3,326
Traffic Flow Prediction With Big Data: A Deep Learning Approach
Lv, Y., Duan, Y., Kang, W., Li, Z., & Wang, F.-Y. (2014) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2014.2345663 · Cited by 3,000
Data fusion in intelligent transportation systems: Progress and challenges – A survey
Faouzi, N.-E. E., Leung, H., & Kurian, A. (2011) · Information Fusion · doi:10.1016/j.inffus.2010.06.001 · Cited by 444
Road Traffic Forecasting: Recent Advances and New Challenges
Lana, I., Del Ser, J., Velez, M., & Vlahogianni, E. I. (2018) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2018.2806634 · Cited by 367
Enhancing transportation systems via deep learning: A survey
Wang, Y., Zhang, D., Liu, Y., Dai, B., & Lee, L. H. (2019) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.12.004 · Cited by 312
Metadata
- Authors
- Okutani, I., & Stephanedes, Y. J.
- Venue
- Transportation Research Part B: Methodological
- Publisher
- Elsevier BV
- Published
- 1984-02
- Volume
- 18
- Issue
- 1
- Pages
- 1-11
- ISSN
- 0191-2615 (ISSN-L)
- OpenAlex
- W2090192376
- Cited by
- 1,104
- References
- 1
- FWCI
- 4.05
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Dynamic prediction of traffic volume through Kalman filtering theory. https://app.cochat.ai/papers/10.1016/0191-2615(84)90002-x
- The paper
- Okutani, I., & Stephanedes, Y. J. (1984). Dynamic prediction of traffic volume through Kalman filtering theory. Transportation Research Part B: Methodological. https://doi.org/10.1016/0191-2615(84)90002-x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
