Empirical research of agricultural enterprise risk warning based on BP neural network model

Author

Hongxia, Zhang ; Yinsheng, Yang ; Hongpeng, Guo

Author_Institution

Key Lab. of Bionic Eng, Jilin Univ., Changchun, China

fYear

2011

fDate

23-25 May 2011

Firstpage

3038

Lastpage

3043

Abstract

The enterprise may check the crisis in the bud through the risk early-warning, thus enabling the enterprise to achieve the sustainable development. Agricultural enterprise is the foundation of agricultural development. Due to their weakness and the particularity of the production process, the risk of agricultural enterprise is more complex, making the risk early-warning of agricultural enterprise more important. In this paper, neural network method is used to make an empirical analysis of risk early-warning of agricultural enterprise, research results show that neural network analysis method is a more scientific and reasonable method for quantitative analysis carried on the risk assessment and the early warning to the agricultural enterprise.

Keywords

agricultural engineering; backpropagation; neural nets; risk management; BP neural network model; agricultural development; agricultural enterprise risk warning; empirical analysis; production process; quantitative analysis; risk assessment; risk early warning; sustainable development; Analytical models; Artificial neural networks; Indexes; Neurons; Production; Risk management; Training; Agricultural Enterprises; BP Neural Network Model; Risk Early-warning;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2011 Chinese

Conference_Location

Mianyang

Print_ISBN

978-1-4244-8737-0

Type

conf

DOI

10.1109/CCDC.2011.5968775

Filename

5968775