Analyzing Traffic Accident Causations in China Based on Neural Network Combined Tsinghua University

Format:

Conference/Event

Author/Creator:

Jun, Xu, author.

Conference Name:

SAE World Congress & Exhibition (2008-04-14 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2008

Summary:

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[18] 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

Notes:

Vendor supplied data

Publisher Number:

2008-01-0533

Access Restriction:

Restricted for use by site license