Road traffic system is a complicated non-linear system, in which road traffic accident is considered as the behavioral characteristic variable, whose developmental changes have trends of increase and stronger random fluctuation. Considering this point, we establish a combination forecasting model (namely GNN) based on grey forecasting model and ANN. First, grey information renewal GM (1,1) is established based on GM (1,1) and used to forecast the change tendency, then BP network is applied to modify grey residuals to capture stochastic phenomenon. The results show that the dual character of the road traffic time series with trends of increase and random fluctuation can be better described. Meanwhile, with advantages of GM (1,1) and ANN, GNN has obtained better forecasting precision than single grey information renewal GM (1,1). In summary, GNN can be applied as a novel, practical and simple forecasting tool in road traffic accident forecasting.
An Information Renewal GNN Model for Road Traffic Accident Forecasting
Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China
2009-07-29
Conference paper
Electronic Resource
English
Highways and roads , Information technology (IT) , Transportation management , Traffic accidents , Construction , Freight transportation , Water transportation , Air transportation , Rail transportation , Errors , Forecasting , Optimization , Information management , Public transportation , Models , Traffic management
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