Increasing the Accuracy of a Deep Learning Model for Traffic Accident Severity Prediction by Adding a Temporal Category
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56950-0_10
Reference15 articles.
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2. Beshah, T., Ejigu, D., Krömer, P., Plato, J., Abraham, A.: Learning the classification of traffic accident types. In 2012 Fourth International Conference on Intelligent Networking and Collaborative Systems, pp. 463–468. IEEE (2012)
3. Amiri, A.M., Sadri, A., Nadimi, N., Shams, M.: A comparison between artificial neural network and hybrid intelligent genetic algorithm in predicting the severity of fixed object crashes among elderly drivers. Accid. Anal. Prev. 138, 105468 (2020)
4. Ezenwa, A.O.: Trends and characteristics of road traffic accidents in Nigeria. J. R. Soc. Health 106(1), 27–29 (1986)
5. Li, K., Xu, H., Liu, X.: Analysis and visualization of accidents severity based on LightGBM-TPE. Chaos, Solitons Fractals 157, 111987 (2022)
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