Research on Enterprise Financial Risks Evaluation Based on the Gray Relevance Theory

Author

Zheng Xie

Author_Institution

Hunan City Univ. Yiyang, Yiyang, China

fYear

2014

fDate

25-26 Oct. 2014

Firstpage

513

Lastpage

516

Abstract

In order to prevent the financial risks of enterprises effectively, the risks evaluation is of great importance. This paper analyses the main factors that affect enterprise financial risks by using the T-test and nonparametric test in statistical software SPSS15.0 and the gray relevance theory (GRA). These factors are considered as the input variables of BP neural network and 56 enterprises are selected as samples to be trained and tested. The results show that featured by fast speed and high prediction accuracy, this model serves as an efficient and practical method for the evaluation of enterprise financial risks in our country.

Keywords

backpropagation; financial management; grey systems; neural nets; nonparametric statistics; risk analysis; statistical testing; BP neural network; GRA; SPSS15.0 statistical software; enterprise financial risk evaluation; enterprise financial risk prevention; gray relevance theory; input variables; nonparametric test; t-test; Accuracy; Analytical models; Correlation; Indexes; Mathematical model; Neural networks; Training; BP neural network; evaluation; financial risks; gray relevance;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4799-6635-6

Type

conf

DOI

10.1109/ICICTA.2014.130

Filename

7003593