The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A review of neural networks applied to transport
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Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
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
Chang, L.-Y. (2005) · Safety Science · doi:10.1016/j.ssci.2005.04.004 · Cited by 344
Neural network based temporal feature models for short-term railway passenger demand forecasting
Tsai, T.-H., Lee, C.-K., & Wei, C.-H. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.02.071 · Cited by 211
A real-time passenger flow estimation and prediction method for urban bus transit systems
Zhang, J., Shen, D., Tu, L., Zhang, F., Xu, C., Wang, Y., Tian, C., Li, X., Huang, B., & Li, Z. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2686877 · Cited by 130
Forecasting the Suez Canal traffic: A neural network analysis
Mostafa, M. M. (2004) · Maritime Policy & Management · doi:10.1080/0308883032000174463 · Cited by 72
Metadata
- Authors
- Dougherty, M.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 1995-08
- Volume
- 3
- Issue
- 4
- Pages
- 247-260
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2165456507
- Cited by
- 434
- References
- 1
- FWCI
- 7.66
- 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: A review of neural networks applied to transport. https://app.cochat.ai/papers/10.1016/0968-090x(95)00009-8
- The paper
- Dougherty, M. (1995). A review of neural networks applied to transport. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/0968-090x(95)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.
