1 |
Berson, A., Smith, S. and Thearling, K. (2000). Building data mining applications for CRM, McGraw-Hill, New York.
|
2 |
Freund, Y. and Mason, L. (1999). The alternating decision tree learning algorithm. In ICML, 99, 121-133.
|
3 |
Heo, M. H. and Lee, Y. G. (2008). Data mining modeling and example, Hannarae, Seoul.
|
4 |
Kwon, G. B. (2003). Bearing capacity estimation of subgrade for frost heaving effect, Incheon National University, Incheon.
|
5 |
Kim, N. S., Nam, Y. K., Cho, G. T. and Lee, B. W. (2011). An establishment of database for effective design of anti-frost heave layer using field data. Korean Society of Hazard Mitigation, 11, 43-47.
DOI
|
6 |
Kim, Y. J., Yu, J. and Kim, H. M. (1999). A study on the frost penetration depth and insulation methods in pavement, Korea Institute of Civil Engineering and Building Technology, Goyang.
|
7 |
Lee, J. Y. and Kim, H. J. (2014). Identification of major risk factors association with respiratory diseases by data mining. Journal of the Korean Data & Information Science Society, 25, 373-384.
DOI
|
8 |
Lee, M. S., Heo, T. Y., Park, H. M. and Kim, B. I. (2012). Development of model for structural evaluation of anti-freezing layer. Journal of the Korean Society of Road Engineers, 14, 25-32.
|
9 |
Quinlan, J. R. (1993). C4.5: Programs for machine learning, Morgan-Kaufmann Publishers, San Mateo, CA.
|
10 |
Shin, E. C., Lee, J. S. and Cho, G. T. (2011). A study on the frost penetration depth of pavement with field temperature data. Journal of the Korean Society of Road Engineers, 13, 21-32.
|
11 |
Nam, Y. K., Park, C. B., Cho, G. T. and Jin, J. H. (2002). The field data on behavior characteristics of anti-frost heave layer. International Journal of Highway Engineering, 4, 19-23.
|