Title :
The computational rules extractor in the detection of tax evasion
Author :
Yi-Zeng Hsieh;Mu-Chun Su;Addison Y.S. Su;Wu-Rong Shih;Jen-Chih Yu;Chien-Yeh Huang
Author_Institution :
Department of Management and Information Technology, Southern Taiwan University of Science and Technology, Taiwan
Abstract :
It is a serious problem of tax evasion in all domains. Because of the narrow human factors, there are case-by-case basis not to examine reported tax cases. Hence, it is a very demanding challenge to grow an effective tax evasion detection mechanism. In this paper, we use the proposed rule extractor approaches (PFHRCNN) to detect tax evasion. The experiment results show the proposed PFHRCNN for tax evasion detection systems is a good way.
Keywords :
"Neural networks","Feature extraction","Companies","Testing","Principal component analysis","Optimization"
Conference_Titel :
Security Technology (ICCST), 2015 International Carnahan Conference on
Print_ISBN :
978-1-4799-8690-3
Electronic_ISBN :
2153-0742
DOI :
10.1109/CCST.2015.7389679
