The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Utilizing support vector machine in real-time crash risk evaluation
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Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
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A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
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WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility
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Cited by
Real-time crash risk prediction on arterials based on LSTM-CNN
Li, P., Abdel-Aty, M., & Yuan, J. (2020) · Accident Analysis & Prevention · doi:10.1016/j.aap.2019.105371 · Cited by 394
Self-citationArtificial intelligence techniques for driving safety and vehicle crash prediction
Halim, Z., Kalsoom, R., Bashir, S., & Abbas, G. (2016) · Artificial Intelligence Review · doi:10.1007/s10462-016-9467-9 · Cited by 110
Jo, Y., Jang, J., Ko, J., & Oh, C. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3156923 · Cited by 30
Metadata
- Authors
- Yu, R., & Abdel-Aty, M.
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 2013-03
- Volume
- 51
- Pages
- 252-259
- ISSN
- 0001-4575 (ISSN-L)
- OpenAlex
- W2022714541
- Cited by
- 317
- References
- 25
- FWCI
- 24.78
- Type
- journal article
- Language
- en
- Open access
- green
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- Yu, R., & Abdel-Aty, M. (2013). Utilizing support vector machine in real-time crash risk evaluation. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2012.11.027
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.