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http://dx.doi.org/10.6106/KJCEM.2021.22.5.029

Affinity Analysis Between Factors of Fatal Occupational Accidents in Construction Using Data Mining Techniques  

Lim, Jiseon (Department of Civil and Environmental Engineering, Incheon National University)
Han, Sanguk (Department of Civil and Environmental Engineering, Hanyang University)
Kang, Youngcheol (Department of Architecture and Architectural Engineering, Yonsei University)
Kang, Sanghyeok (Department of Civil and Environmental Engineering, Incheon National University)
Publication Information
Korean Journal of Construction Engineering and Management / v.22, no.5, 2021 , pp. 29-38 More about this Journal
Abstract
Governments and companies are trying to reduce occupational accidents in the construction industry; however, the number of disasters are not decreasing significantly. This study aims to identify the correlation between factors affecting construction disasters quantitatively. To this end, 1,197 cases of serious disasters provided by Korea Occupational Safety and Health Administration (KOSHA) were analyzed using affinity analysis, one of the data mining techniques. The data from KOSHA were preprocessed and analyzed with variables of accident type, project type, activity type, original cause materials, sensory temperature, time of the accident, and fall height, and the association rules were derived for fall accidents and the others. For fall accidents, 64 association rules with lift ratios of 1.38 or greater were derived, and for the other accidents, 59 association rules with lift ratios of 1.54 or greater were derived. After analyzing the derived association rules focusing on the relationship among accident factors, this study presented the significance of applying the affinity analysis to address the study's limitations. The significance of this study can be found in that the correlation among factors affecting construction accidents is presented quantitatively.
Keywords
Construction Occupational Accident; Affinity Analysis; Association Rules; Data Mining; Construction Safety; Safety Management;
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  • Reference
1 Korea Occupational Safety and Health Administration (KOSHA). (2016). "Guidelines on occupational accidents recorded and classified." KOSHA GUIDE G - 83 - 2016.
2 Korea Occupational Safety and Health Administration (KOSHA). (2020). "2019 industrial accident status analysis."
3 Cho, Y.R., Kim. Y.C., and Shin. Y.S. (2017). "Prediction Model of Construction Safety Accidents using Decision Tree Technique." Journal of the Korea Institute of Building Construction, 17(3), pp. 295-303.   DOI
4 Choi, J.H., and Ryu, H.G. (2019). "Analysis of Occupational Injury and Feature Importance of Fall Accidents on the Construction Sites using Adaboost." Journal of the Arcotectiral Institute of Korea Structure & Construction, 35(11), pp. 155-162.
5 Ministry of Land, Infrastructure and Transport (MoLIT). (2020). "Enforcement Decree of the Framework Act on Construction Industry." Law No. 31516.
6 Kim, Y.C., Yoo. W.S., and Shin. Y.S. (2017). "Application of Artificial Neural Networks to Prediction of Construction Safety Accidents." The Journal of the Korean Society of Hazard Mitigation, 17(1), pp. 7-14.   DOI
7 Lee, G.H., Lee, C.S., Koo, C.W., and Kim, T.W. (2020). "Identification of Combinatorial Factors Affecting Fatal Accidents in Small Construction Sites: Association Rule Analysis." Korean Journal of Construction Engineering and Management, KICEM, 21(4), pp. 90-99.   DOI
8 Leem, Y.M., and Choi, Y.H. (2005). "Selection of an Optimal Algorithm among Decision Tree Techniques for Feature Analysis of Industrial Accident in Construction Industries." Journal of the Korea Safety Management & Science, 7(5), pp. 1-8.
9 Lee, K.H. (2016). "An Analysis on the Correlation Between Climate Factors and Fatal Accident in Construction Site." MS Thesis, Semyung University.
10 Lee, G.Y. (2020). "Association Rule Mining Approach to Extracting Relationships of Accident Factors in Construction Sites." MS Thesis, Pukyong University.
11 Min, Y.E., Cho, S.J., Ji, H.J., Yoo, W.S., and Shin, Y.S. (2018). "Predicting Model for Occupational Disease using Complex Analysis in Construction Site." The Korean Society of Science & Art, 36, pp. 109-120.   DOI
12 Shmueli, G., Bruce, P.C., Yahav, I., Patel, N.R., and Lichtendahl Jr. K.C. (2018). "Data Mining for Business Analytics", Wiley.
13 Son, K.Y., and Ryu, H.G. (2019). "Association Rules Analysis of Safe Accidents Caused by Falling Objects." Journal of the Korea Institute of Building Construction, 19(4), pp. 341-350.   DOI
14 Shin, D.P., Son, C.B., and Lee, D.E. (2012). "Association Analysis of Construction Accident Attributes Causing Fatalities." Journal of the Architectural Institute Of Korea Structure & Construction, 28(2), pp. 87-94.   DOI