Zheng, M., Li, T., Zhu, R., Chen, J., Ma, Z., Tang, M., Cui, Z., & Wang, Z. (2019). Traffic accident's severity prediction: A deep-learning approach-based CNN network. IEEE Access, 7, 45613-45620.
https://doi.org/10.1109/ACCESS.2019.2903319.
Soltani, A., Alaedini, F., Shamspour, N., & Ahmadi Marzaleh, M. (2021). Hazard assessment of Iran provinces based on the Health Ministry tool in 2019. Iran Red Crescent Medical Journal, 23(1), e204. https://doi.org/10.32592/ircmj.2021.23.1.204
Zhang, J.H. (2019). Integration Theory and Optimal Application of the Traffic Accident Management System. In Proceedings of the International Conference on Cyber Security Intelligence and Analytics (CSIA), Shenyang, China, February 2019; Springer International Publishing Ag: Shenyang, China, 2019; pp. 99–104. DOI:
10.1007/978-3-030-15235-2_16
Astarita, V., Shaffiee Haghshenas, S., Guido, G., & Vitale, A. (2023). Developing new hybrid grey wolf optimization-based artificial neural network for predicting road crash severity. Transportation Engineering, 12, 100164.
https://doi.org/10.1016/j.treng.2023.100164
Goli, A., & Malmir, B. (2019, May 4). A covering tour approach for disaster relief locating and routing with fuzzy demand. International Journal of Intelligent Transportation Systems Research.
https://doi.org/10.1007/s13177-019-00185-2
Shang, Q., Feng, L., & Gao, S. (2020). A hybrid method for traffic incident detection using Random Forest-Recursive Feature Elimination and Long Short-Term Memory network with Bayesian Optimization Algorithm. IEEE Access, 8,223513-223522.
https://doi.org/10.1109/ACCESS.2020.3047340.
Guo, Y., Jena, R., Hughes, D., Lewis, M., & Sycara, K. (2021). Transfer learning for human navigation and triage strategies prediction in a simulated urban search and rescue task.
Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA), 1-8.
https://doi.org/10.1109/ICRA48506.2021.9562203
Yang, J., Wang, P., Yuan, W., Ju, Y., Han, W., & Zhao, J. (2021). Automatic generation of optimal road trajectory for the rescue vehicle in case of emergency on mountain freeway using reinforcement learning approach. IET Intelligent Transport Systems, 15(10), 1281–1289. https://doi.org/10.1049/itr2.12037
Zhao, W., Yang, Y., & Lu, Z. (2022). Interval short-term traffic flow prediction method based on CEEMDAN-SE noise reduction and LSTM optimized by GWO. Wireless Communications and Mobile Computing, 2022, Article ID 5257353, 16 pages.
https://doi.org/10.1155/2022/5257353
Wang, D., Peng, J., Zhao, J., Teng, Y., Xue, W., & Tao, X. (2023, October 10–13). Dual-Transformer: A general model for traffic accident prediction. In 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall). IEEE.
https://doi.org/10.1109/VTC2023-Fall60731.2023.10333613
Mousavi, B.S., Jahangir, E., Neysani Samani, N., & Argany, M. (2023). Spatial Analysis of Rescue and Relief Bases in Alborz Province in order to Reduce Hazards. Sci J Rescue Relief, 2023; 15(3): 194- 206. acceptance: 27 Jun. 2023. Doi: 10.32592/jorar.2023.15.3.5.
Al-Thani, M. G., Sheng, Z., Cao, Y., & Yang, Y., "Traffic Transformer: Transformer-based framework for temporal traffic accident prediction," AIMS Mathematics, vol. 9, no. 5, pp. 12610–12629, Apr. 2024. doi: 10.3934/math.2024617.
Huang, G., Qi, Y., Cai, Y., Luo, Y., & Huang, H. (2024). A Grey Wolf Optimizer Algorithm for Multi-Objective Cumulative Capacitated Vehicle Routing Problem Considering Operation Time. Biomimetics, 9(6), 331.
https://doi.org/10.3390/biomimetics9060331
Forouzandeh, M., Mousavi, B. S., Neysani, N., & Argany, M. (2025). Spatial prediction of the impact of road accidents on traffic using machine learning algorithms. Earth Observation and Geomatics Engineering, 8(1), 29–47.
https://doi.org/10.22059/eoge.2025.378825.1155
Jiang, Y., Qu, X., Zhang, W., Guo, W., Xu, J., Yu, W., & Chen, Y. (2025). Analyzing crash severity: Human injury severity prediction method based on transformer model. Vehicles, 7(1), 5. https://doi.org/10.3390/vehicles7010005
Peng, D., & Yan, W. (2025). Test-Time Training with Adaptive Memory for Traffic Accident Severity Prediction. Computers, 14(5), 186. https://doi.org/10.3390/computers14050186
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention Is All You Need. Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
https://doi.org/10.48550/arXiv.1706.03762
Wu, H., Xu, J., Wang, J., & Long, G. (2021). Auto former: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. Advances in Neural Information Processing Systems, 34.
https://doi.org/10.48550/arXiv.2106.13008
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