Title :
Combined forecasting of the vehicle holdings based on gray-neural network
Author :
Wang Jun ; Teng Yufa ; Liu Ying ; Yang Dianhua
Author_Institution :
Dept. of Aviation Ammunition, Air Force Logistics Coll., Xuzhou, China
Abstract :
The boom of automobile industry has injected vigor into the national economy, but it has also imposed great pressure on the healthy development of social economy and the protection of ecological environment. This paper sets up gray forecast model and BP neural network model for related factors that affect the private vehicle holdings. Based on the models, it introduces the concept of model validity from the point of model forecasting precision to optimize the model for acquiring maximum validity, establishes a combined gray-neural network forecasting model, and predicts the holdings of private vehicles respectively. The result indicates that the combined forecasting model is more precise and provides a better way to settle the problem of forecasting private vehicle holdings.
Keywords :
backpropagation; forecasting theory; neural nets; road vehicles; transportation; BP neural network model; automobile industry; ecological environment protection; gray forecast model; gray-neural network forecasting model; private vehicle holding forecasting; Accuracy; Biological system modeling; Forecasting; Mathematical model; Neural networks; Predictive models; Vehicles; BP neural network; gray forecasting; validity; vehicle holdings; weight coefficient;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161895