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Analyzing Traffic Accident Causations in China Based on Neural Network Combined
Technical Paper
2008-01-0533
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Clarifying accident causations can provide a strong foundation to prevent traffic accidents and reduce severities. This paper uses Chinese government census data from 1996-2003[1∼8] and models a relationship between various kinds of traffic accident causations and the severities of the traffic accidents based on neural network combined (NNC). The paper adapts multi-folder cross validation concept to enhance the properties of NNC. It then conducts sensitivity analysis on the trained NNC to identify the prioritized importance of traffic accident causations as they are to the severities of traffic accident. Lastly, the results are validated and compared by the findings of previous researches.
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Citation
Jun, X. and Yibing, L., "Analyzing Traffic Accident Causations in China Based on Neural Network Combined," SAE Technical Paper 2008-01-0533, 2008, https://doi.org/10.4271/2008-01-0533.Also In
References
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- Traffic management bureau, Police ministry Annual census of traffic accident in People's Republic of China May 2004
- Traffic management bureau, Police ministry Annual census of traffic accident in People's Republic of China May 2003
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