The Research of Tax Inspection Based on Generalized Regression Neural Network

Shihong Chen¹, Xiaoqing Liu²

¹Guangdong University of Foreign Studies, Guangzhou, China.
²Jinan University, Guangdong University of Finance, Guangzhou, China.

DOI: 10.4236/oalib.1100949                

Abstract

This paper tries to use the generalized regression neural network (in short: GRNN) to assist tax inspection case selection. First, this paper briefly introduces the theory of generalized regression neural network and applies it in the tax inspection. Second, it analyzes the financial statements and tax returns of 93 commercial enterprises, and then establishes the GRNN model and gets the analyzing result. Finally, the result is compared with the known taxation case. Then we get the conclusion that the generalized regression neural network method can help the tax inspection case selection and improve the efficiency and effectiveness of inspection work.

Keywords

Tax Inspection, Generalized Regression Neural Network

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	He, Z. (2007) On the Reform Tendency of Tax Inspection System of China in the New Situation. Southwestern University of Finance and Economics, Chengdu.
[2]	Specht, D.F.A. (1991) General Regression Neural Network. IEEE Transaction on Neural Networks, 2, 568-576. http://dx.doi.org/10.1109/72.97934
[3]	(2010) 30 Case Study of MATLAB Neural Network. Beihang University Press, Beijing.
[4]	Chen, Y. (2004) Research on Sampling of Tax-Checking. Tianjin University, Tianjin.
[5]	Guan, X. (2005) Data Mining Research on Sampling of Tax-Checking. Liaoning Technical University, Fuxin.
[6]	Scott, D.W. (1992) Multivariate Density Estimation: Theory, Practice and Visualization. Wiley, New York, 45-67. http://dx.doi.org/10.1002/9780470316849
[7]	Chen, S.H. and Zhang, Y.M. (2009) Application of Binary Logistic Regression Analysis in Tax Inspection. Financial Computer of Huanan, 6, 48-49.