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    Abstract
2013 (Vol. 6, Issue: 21)
Article Information:

The Comparison on for Traffic Accident Forecasting in Long and Short Period Based on Multi-layer Recursive Forecasting Method

Yu-Rende, Zhang Qiang, Zhang-Xiaohong and Huo-Lianxiu
Corresponding Author:  Yu-Rende 

Key words:  Auto regression, environmental factors, forecasting, long period, multi-layer recursive, road traffic accident, short period
Vol. 6 , (21): 4052-4057
Submitted Accepted Published
January 26, 2013 March 02, 2013 November 20, 2013
Abstract:

The multi-layer recursive forecasting method is used on road traffic accident forecasting in this study. We suggested the factors as density of population, GDP per capita, highway passenger transport, highway freight volume, highway mileage, density of road network, amount of vehicle, amount of cars per capita and environmental factors is selected by MATLAB in forecasting model. The model including autoregression item and the model including autoregression item and environmental factors is proposed. By changing the forecasting period, the forecasting results in years and months are acquired and analyzed. We conclude that the forecasting accuracy in short period is higher than in long period by comparing with results of long and short period.
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  Cite this Reference:
Yu-Rende, Zhang Qiang, Zhang-Xiaohong and Huo-Lianxiu, 2013. The Comparison on for Traffic Accident Forecasting in Long and Short Period Based on Multi-layer Recursive Forecasting Method.  Research Journal of Applied Sciences, Engineering and Technology, 6(21): 4052-4057.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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