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Architecture & Urban Research Institute

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ÀúÀÚ¸í Á¶¿¹¸²½Äº°ÀúÀÚ ; ±è¿¬Ã¶ ; ½ÅÀ±¼®½Äº°ÀúÀÚ
¹ßÇà»ç Çѱ¹°ÇÃà½Ã°øÇÐȸ
¼ö·Ï»çÇ× Çѱ¹°ÇÃà½Ã°øÇÐȸ ³í¹®Áý, Vol.17 No.3 (2017-06)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(295) ÃÑÆäÀÌÁö(9)
ISSN 15982033
ÁÖÁ¦ºÐ·ù ½Ã°ø(Àû»ê)
ÁÖÁ¦¾î ; decision tree ; construction safety accidents ; prediction model
¿ä¾à2 Over the past 7 years, the number of victims of construction disasters has been gradually increasing. Compared with projects in other industries, construction projects are highly exposed to safety risks. For this reason, the research methods of predicting and managing the risk of construction disasters are urgently needed that can be applied to a construction site. This study aims to propose a prediction model for a construction disaster using the decision tree technique. The developed the model is reviewed the applicability by evaluating its accuracy based on disaster data. The top three of the prediction values obtained from the proposed model were enumerated, and then the cumulative accuracy were also calculated. The prediction accuracy was 40 percent for the first value, but the cumulative accuracy was 80 percent. Thus, as more disaster data was accumulated, the cumulative accuracy appeared to be higher. If utilized in construction sites, the model proposed in this study would contribute to a reduction in the rate of construction disasters.
¼ÒÀåó Çѱ¹°ÇÃà½Ã°øÇÐȸ
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DOI https://doi.org/10.5345/JKIBC.2017.17.3.295
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