DocumentCode :
532947
Title :
Study on Early Warning against Risk in rapeseed industry of China based on BP Neural Network
Author :
Wang, Jingxian ; Wu, Qinghua
Author_Institution :
Economic Dept., Huazhong Univ. of Sci. of Tecknology, Wuhan, China
Volume :
15
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
For the influence from the supply and demand and the factors that affect the rapeseed industry such as the macroeconomic factors, national policy and international market price and so on, this article makes up the index system of the Early Warning against Risk of market price of China by using the fluctuation ratio of rapeseed procurement price as index of the Early Warning against Risk in the rapeseed industry. By using the samples from 1990 to 2007, and by empirical study of the early warning against risk of rapeseed industry through the BP Neural Network, this article verifies the practicability and feasibility of the Early Warning model against Risk of BP Neural Network, which make the future Early Warning against Risk of Rapeseed Industry possible.
Keywords :
agriculture; backpropagation; market research; neural nets; pricing; procurement; risk analysis; BP neural network; China; early-warning-against-risk model; international market price; macroeconomic factors; market price; national policy; rapeseed industry; rapeseed procurement price; supply and demand; Agriculture; Business; Computer languages; Neural networks; BP Neural Network; Rapeseed Industry; the Early Warning against Risk;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5622575
Filename :
5622575
Link To Document :
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