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The statistical factors affecting the freezing of the road pavement
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 Title & Authors
The statistical factors affecting the freezing of the road pavement
Kim, Hyun-Ji; Lee, Jea-Young; Kim, Byung-Doo; Cho, Gyu-Tae;
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Due to the character of the climate of Korea, the pavement of a road is Influenced by freezing in winter season and thawing in thawing season. In the last few years, several articles have been devoted to the study to minimize the damage of freezing and thawing action. The purpose of this paper is to identify appropriacy of factors that influence road pavement thickness. We conduct the decision tree analysis on the field data of road pavement. The target variable is `Frost penetration`. This value was calculated from the temperature data. The input variables are `Region`, `Type of road pavement`, `Anti-frost layer`, `Month` and `Air temperature`. The region was divided into 9 regions by freezing index , , . The type of road pavement has three-section such as area of cutting, boundary area of cutting and bankin, lower area of banking. As the result, the variables that influence `Frost penetration` are Month, followed by anti-frost layer, air temperature and region.
Decision tree;field measurement;frost penetration;road pavement;
 Cited by
Berson, A., Smith, S. and Thearling, K. (2000). Building data mining applications for CRM, McGraw-Hill, New York.

Freund, Y. and Mason, L. (1999). The alternating decision tree learning algorithm. In ICML, 99, 121-133.

Heo, M. H. and Lee, Y. G. (2008). Data mining modeling and example, Hannarae, Seoul.

Kwon, G. B. (2003). Bearing capacity estimation of subgrade for frost heaving effect, Incheon National University, Incheon.

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. crossref(new window)

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.

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. crossref(new window)

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.

Quinlan, J. R. (1993). C4.5: Programs for machine learning, Morgan-Kaufmann Publishers, San Mateo, CA.

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.

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.