A Model of Injury Severity Prediction in Traffic Accident Based on GA-BP Neural Network
A Model of Injury Severity Prediction in Traffic Accident Based on GA-BP Neural Network
- Neue Suche nach: Wang, Shuang
- Neue Suche nach: Wei, Chong
- Neue Suche nach: Wei, Yansha
- Neue Suche nach: Wang, Wenzhe
- Neue Suche nach: Wu, Fei
- Neue Suche nach: Wang, Shuang
- Neue Suche nach: Wei, Chong
- Neue Suche nach: Wei, Yansha
- Neue Suche nach: Wang, Wenzhe
- Neue Suche nach: Wu, Fei
Understanding the non-linear relationship between traffic injury severity and factors in accuracy can help decrease accident occurrence and improve driving safety. This paper uses a GA-BP neural network to model the relationship and predict injury severity in traffic accidents classified into fatality, serious crash, and slight crash. And it validates the superior performance of GA-BP with crash data from the UK in 2015, compared to the BP neural network and the logistic regression model. A sensitivity analysis is applied to find out the contribution that input variables have on injury severity. This paper indicates that the GA-BP neural network provides a reference for injury severity prediction in traffic accident.
Dokumentinformationen
A Model of Injury Severity Prediction in Traffic Accident Based on GA-BP Neural Network
19th COTA International Conference of Transportation Professionals ; 2019 ; Nanjing, China
CICTP 2019 ; 2470-2481
2019-07-02
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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