NDLI: Research on sampling method of tax-checking based on neural network

Content Provider	IEEE Xplore Digital Library
Author	Wang Guang-liang
Copyright Year	2012
Description	Author affiliation: School of Management, Harbin Institute of Technology, China, 150001 (Wang Guang-liang)
Abstract	It is a core component of the Golden Tax Project that the application of information technology supports the tax-checking. According to some problems of inefficiency and poor accuracy in tax-checking sampling practices, learning from the current tax-checking sampling study, selects financial indicators of tax-checking sample of the value-added tax (VAT) based on gradually discriminant analysis (GDA), has a better solution to discriminant classifier of the “honest tax group” and “dishonest tax group”, and then using the technology of self-organizing map neural network (SOM), builds a intelligent analysis model on VAT sampling; Finally, uses the real data of 43 enterprises as an example to test, Finally, the use of 43 actual business data as an example the test, and the results of discriminant analysis were compared with that of statistical analysis, and the results show that the sampling effect of BP nets is remarkable.
Starting Page	1541
Ending Page	1546
File Size	293115
Page Count	6
File Format	PDF
ISBN	9781467330152
ISSN	21551855
e-ISBN	9781467330145
DOI	10.1109/ICMSE.2012.6414378
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models Accuracy Statistical analysis data mining (DM) sampling Neural networks gradually discriminant analysis (GDA) self-organizing mapping (SOM) Marketing and sales Indexes tax check
Content Type	Text
Resource Type	Article

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