1. 財政部賦稅署 (1993),營利事業所得稅查核技術之研究。
2. 高雄市國稅局 (1994),從營利所得稅逃漏型態論行政罰法之改進。
3. 胡秀杏,營利事業所得稅逃漏行為之研究,台灣大學商研所碩士論文,民國七十六年。4. 陳順宇,多變量分析,華泰書局,民國八十七年。
5. 葉怡成 (1999),應用類神經網路,儒林書局,台北。
6. 盧欽滄 (1994),稅務調查與間接證明法兼論租稅詐欺,凱侖出版社,台北。
7. 蘇木春、張孝德 (2000),機器學習:類神經網路、模糊數學及基因演算法則,全華科技圖書公司,台北。
8. 蘇碧霞 (1991),租稅違章逃漏查緝之研究,七十八年度公教人員出國專題研究報告。
9. Altman, E. (1993), Corporate Financial Distress and Bankruptcy, John Wiley & Sons, New York.
10. Bentz, Y. and D. Merunka (2000), “Neural networks and the multinomial logit for brand choice modeling: a hybrid approach,” Journal of Forecasting, 19, pp. 177-200.
11. Chu, C. Y. and L. Tan (1996), “Tax evasion by small business: theory and empirical evidence of Taiwan,” Public Economic Review, 1, pp. 157-183.
12. Haykin, S. (1999), Neural Network: A Comprehensive Foundation, Second Edition, Prentice Hall, Englewood Cliffs, NJ.
13. Hunter, W. J. and M. A. Nelson (1996), “An IRS production function,” National Tax Journal, 49, pp. 105-115.
14. Johnson R. A. and D. W. Wichern (1998), Applied Multivariate Statistical Analysis, Fourth Edition, Prentice Hall, Englewood Cliffs, NJ.
15. Jonathan, R. M., E. Pednault, and M. Sudan (1997), “A statistical perspective on data mining,” Future Generation Computer Systems, 13, pp. 117-134.
16. McKee, T. E. and M. Greenstein (2000), “Predicting bankruptcy using recursive partitioning and a realistically proportioned data set,” Journal of Forecasting, 19, pp. 219-230.
17. Neter, J., M. H. Kutner, C. J. Nachtsheim, and W. Wasserman (1996), Applied Linear Statistical Models, Fourth Edition, IRWIN, Chicago.
18. Ohlson, J. (1980), “Financial ratios and probabilistic prediction of bankruptcy,” Journal of Accounting Research, 18, pp. 109-131.
19. SAS Institute Inc. (1997), SAS/STAT Software: Changes and Enhancements through Release 6.12, SAS Institute Inc., Cary, NC.
20. SPSS Inc. (2002), http://www.spss.com/spssbi/ applications/fraud/index.htm.
21. Sung, T. K., N. Chang, and G. Lee (1999), “Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction,” Journal of Management Information Systems, 16, pp. 63-85.
22. Webley, P., M. Cole, and O. Eidjar ( 2001), “The prediction of self-reported and hypothetical tax-evasion: evidence from England,” France and Norway Journal of Economic Psychology, 22, pp. 141-155.
23. Westphal, C. and T. Blaxton (1998), Data Mining Solutions Methods and Tools for Solving Real-World Problems, John Wiley & Sons, New York.