Keywords: machine learning, artificial intelligence, data analysis,
FORECASTING THE SEVERITY OF THE CONSEQUENCES OF ACCIDENTS WITH THE USE OF METHODS OF MACHINE LEARNING
UDC 681.3 Н
This article discusses the possibility of developing a model for predicting traffic accidents on the basis of a crash database provided by the State Traffic Safety Inspectorate of Russia. An example of using the collected data to develop a model for predicting the severity of the consequences of an accident is given, and factors influencing this are analyzed.
1. Показатели состояния безопасности дорожного движения (Электронный ресурс - http://stat.gibdd.ru/).
2. Python Data Analysis Library (Элек-тронный ресурс – https://pandas.pydata.org/).
3. scikitlearn (Электронный ресурс – https://scikitlearn.org/stable/).
4. imbalanced-learn (Электронный ре-сурс – https://imbalanced-learn.readthedocs.io/en/stable/).
5. Haibo He, Edwardo A. Garcia “Learn-ing from Imbalanced Data”, IEEE Transac-tions on Knowledge and Data Engineering ( Volume: 21 , Issue: 9 , Sept. 2009 ) (Элек-тронный ресурс – https://ieeexplore.ieee.org/document/5128907/).
6. XGBoost documentation (Электрон-ный ресурс – https://xgboost.readthedocs.io/en/latest/).
Keywords: machine learning, artificial intelligence, data analysis,
For citation: Donchenko D.S. , Sadovnikova N.P. , Parygin D.S. , FORECASTING THE SEVERITY OF THE CONSEQUENCES OF ACCIDENTS WITH THE USE OF METHODS OF MACHINE LEARNING. Bulletin of the Voronezh Institute of High Technologies. 2019;13(4). Available from: https://vestnikvivt.ru/ru/journal/pdf?id=1059 (In Russ).
Published 31.12.2019