Title :
Research on Enterprise Financial Risks Evaluation Based on the Gray Relevance Theory
Author_Institution :
Hunan City Univ. Yiyang, Yiyang, China
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;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-6635-6
DOI :
10.1109/ICICTA.2014.130
