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Comparison of parametric and nonparametric models for traffic flow forecasting
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Citations
Cited by
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
Real-time road traffic prediction with spatio-temporal correlations
Min, W., & Wynter, L. (2011) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2010.10.002 · Cited by 668
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
Short-term traffic flow prediction with Conv-LSTM
Liu, Y., Zheng, H., Feng, X., & Chen, Z. (2017) · 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP) · doi:10.1109/wcsp.2017.8171119 · Cited by 328
Survey on traffic prediction in smart cities
Nagy, A. M., & Simon, V. (2018) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2018.07.004 · Cited by 312
Metadata
- Authors
- Smith, B. L., Williams, B. M., & Keith Oswald, R.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2002-08
- Volume
- 10
- Issue
- 4
- Pages
- 303-321
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2150010190
- Cited by
- 1,006
- References
- 0
- FWCI
- 36.53
- 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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How to cite
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- CoChat. (2026). Citation check: Comparison of parametric and nonparametric models for traffic flow forecasting. https://app.cochat.ai/papers/10.1016/s0968-090x(02)00009-8
- The paper
- Smith, B. L., Williams, B. M., & Keith Oswald, R. (2002). Comparison of parametric and nonparametric models for traffic flow forecasting. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/s0968-090x(02)00009-8
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.
