DocumentCode :
1897406
Title :
The Application of BP Neural Network Principal Component Analysis in the Forecasting the Road Traffic Accident
Author :
Ming, He ; Xiucheng, Guo
Author_Institution :
Coll. of Transp., Southeast Univ., Nanjing, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
107
Lastpage :
111
Abstract :
According to complexity and comprehensibility of factors which affect road traffic safety, we use the method of principal component analysis to refine new factors which are linearly independent, then we forecast road traffic accident according to principal component by BP neural network simulation, analyse the relationship between traffic accident evaluating index and the causes of traffic accident, including people, vehicles, road and environment. At last we applied the method to a case, from the simulated result we can infer that the method of BP neural network simulation principal component analysis is superior to multinomial fitting and BP neural network simulation in the efficiency and precision.
Keywords :
backpropagation; digital simulation; forecasting theory; neural nets; principal component analysis; road accidents; road safety; road traffic; traffic engineering computing; BP neural network simulation; principal component analysis; road traffic accident forecasting; road traffic safety; Analytical models; Independent component analysis; Neural networks; Predictive models; Principal component analysis; Road accidents; Road safety; Telecommunication traffic; Traffic control; Vehicle safety; BP neural network; forecasting; principal component analysis; road traffic accident;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.35
Filename :
5287697
Link To Document :
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