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PA기법을 이용한 건축공사 공종별 사망사고 예측모델 개발에 관한 연구 - 의사결정나무를 중심으로 -
Predictive Analytics Model for Death Accidents in Building Projects by Trade - Based on Decision Tree- 원문보기

한국건설관리학회논문집 = Korean journal of construction engineering and management, v.22 no.5, 2021년, pp.55 - 65  

최정원 (세종대학교 건축학과) ,  김한수 (세종대학교 건축학과)

초록
AI-Helper 아이콘AI-Helper

건설업은 타 산업에 비해 높은 사망사고율을 보이고 있으며, 최근 사망사고에 대한 기업의 법적 책임이 강화되고 있다. 이는 건설사에게 큰 부담이 되고 있으며, 건설 사망사고에 대한 선제적 예측과 관리의 필요성을 증대시키고 있다. 본 연구의 목적은 의사결정나무를 활용하여 건축공사에서 발생할 수 있는 사망사고를 사전에 예측할 수 있는 모델을 개발하는데 있다. 본 연구에서 의미하는 사망사고 예측모델이란 건축공사의 조건에 따라 공종별로 발생할 수 있는 사망사고의 가능성(확률)을 예측하는 모델을 의미한다. 예측모델의 활용을 통한 사망사고에 대한 사전 예측과 선제적 대응은 법적 처벌을 예방하고 건축공사의 성공적인 수행이라는 측면에서 중요한 의의를 지닌다.

Abstract AI-Helper 아이콘AI-Helper

Compared with other industries, construction industry shows a higher rate of death accidents and recently companies' legal responsibilities are to be increasingly enforced. The trend causes tremendous concerns for construction firms and increases the importance of forecasting and pro-actively managi...

주제어

표/그림 (5)

참고문헌 (33)

  1. Bae, S.Y., and Lee, C. (2018). "A Case Study on the Major Accident in Construction Projects." Proceedings of the National University Student Conference, KICEM, 1(13), pp. 48-51. 

  2. Baek, S.J. (2017). "An Predictive Analytics based on GoalScenario for Self-adaptive System." Journal of the Korea Convergence Society, Korea Convergence Society, 8(11), pp. 77-83. 

  3. Bradlow, E.T., Gangwar, M., Kopalle, P., and Voleti, S. (2017). "The Role of Big Data and Predictive Analytics in Retailing." Journal of Retailing, Elsevier, 93(1), pp. 79-95. 

  4. Cho, J.S. (2012). "Inflow and Outflow Analysis of Double Majors using Social Network Analysis." Journal of the Korean Data & Information Science Society, Korean Data & Information Science Society, 23(4), pp. 693-701. 

  5. Cho, K.H., and Park, H.C. (2011). "A Study on Decision Tree Creation using Intervening Variable." Journal of Korean Data Information Science Society, Korean Data Information Science Society, 22(4), pp. 671-678. 

  6. Cho, Y., Kim, Y.C., and Shin, Y. (2017). "Prediction Model of Construction Safety Accidents using Decision Tree Technique." Journal of the Korea Institute of Building Construction, Korean Institute of Building Construction, 17(3), pp. 295-303. 

  7. Choi, S.I., Park, T.J., and Kang, J.G. (2011). "A Study on the Housing Types Selection Expectation in Senescence using a Decision Tree - Focus on the Baby Boom Generation in Pusan." Journal of The Residential Environment Institute of Korea, Residential Environment Institute Of Korea, 9(2), pp. 235-251. 

  8. Frees, E.W., and Gao, L. (2019). "Predictive Analytics and Medical Malpractice." North American Actuarial Journal 24(2), Society of Actuaries pp. 211-227. 

  9. Halper, F. (2014). Predictive Analytics for Business Advantage, TDWI Best Practices Report. 

  10. Hong, A., Ko, J., Yoo, S. (2010). "A Study on the Forecasting Model of the Investment Characteristics of Seoul Office Buildings based on Data Mining." Seoul Studies, Seoul Institute, 11(2), pp. 51-68. 

  11. Howell, D.C. (2010). Fundamental Statistics for Behavioral Sciences, 8th ed, Cengage Learning. 

  12. Hwang, N.H., and Kim, Y.S. (2012). "Modeling and Prediction of Construction Business using Data Mining Technique." Proceedings of the National University Student Conference, KICEM, pp. 40-43. 

  13. Jang, H.D. (2014). "Determinants of Intention to Moving and Remodeling in Small and Medium-Sized Apartments using Decision-tree Analysis." Journal of the Architectural Institute of Korea (JAIK), Architectural Institute Of Korea, 30(9), pp. 45-56. 

  14. Jeong, C, Jeong, W.Y., and Shin, D. (2015). "Selection of the Optimal Decision Tree Model using Grid Search Method : Focusing on the Analysis of the Factors Affecting Job Satisfaction of Workplace Reserve Force Commanders." Journal of the Korean Operations Research and Management Science Society, Korean Operations Research and Management Science Society (KORMS), 40(2), pp. 19-29. 

  15. Jeong, Y.H., and Choi, Y.W. (2014). "A Study on the Analysis of Urban Highways Traffic Accident's Impact Factors based on Building Discriminant Models-In Busan Metropolitan City." Journal of The Korean Society of Civil Engineers, Korean Society of Civil Engineers, 34(4), pp. 1269-1278. 

  16. Kim, E.J. (2020). "Prediction Model for Construction Safety Accidents using Random Forest." Journal of the Regional Association of Architectural Institute of Korea, Regional Association of Architectural Institute of Korea, 22(5), pp. 295-303. 

  17. Kim, H.M., Kim, T.H., Shin, Y.K., Kim, Y.S., and Han, S.W. (2011). "Regression Technique-based Productivity Estimation Conducting Construction Delay Factor Analysis on Interior Works in High-rise Building Construction." Proceedings of the Korean Institute of Building Construction Conference, Korea Institute of Building Construction, 11(1), pp. 323-324. 

  18. Kim, Y.C., Yoo, W.S., and Shin, Y. (2017). "Application of Artificial Neural Networks to Prediction of Construction Safety Accidents." Journal of the Korean Society of Hazard Mitigation, Korean Society of Hazard Mitigation, 17(1), pp. 7-14. 

  19. Koo, K.M., and Kim, C.J. (2015). "Analysis on Participation Factors for Physical Activity of People with Brain Lesion by using Decision Tree Analysis." Journal of Sport and Leisure Studies, Korean Society of Sport and Leisure Studies, 60, pp. 633-643. 

  20. Kweon, Y.R., and Kim, S.Y. (2014). "Predictors of Protective Factors for Internet Game Addiction in Middle School Students using Data Mining Decision Tree Analysis." Journal of Korean Academy of Psychiatric and Mental Health Nursing, Korean Academy of Psychiatric and Mental Health Nursing, 23(1), pp. 12-20. 

  21. Lee, C.H., Hur, J., Oh, H.J., Kim, H.J., Ryu, P.M., and Kim, H.K. (2013). "Technology Trends of Issue Detection and Predictive Analysis on Social Big Data." Electronics and Telecommunications Trends, Electronics and Telecommunications Research Institute, 28(1), pp. 62-71. 

  22. Lee, C.S., Jung, M.N., and Kim, Y.J. (2012). "Predictors of Suicidal Ideation for Korean Middle and High School Students : The Application of Decision Tree Analysis." Studies on Korean Youth, National Youth Policy Institute, 23(1), pp. 31-55. 

  23. Ministry of Employment and Labor (MEL) (2021). Status of Industrial Accidents at the end of December 2020. 

  24. Mishra, N., and Silakari, S. (2012). "Predictive Analytics: A Survey, Trends, Applications, Opportunities & Challenges." International Journal of Computer Science and Information Technologies, AIRCC, 3(3) pp. 4434-4438. 

  25. Oh, J.A., and Oh, H. (2018). "The Predictors of Factors Related to Career Decision Making Amongst Adolescents who drop out of School, using Decision-Making Tree Analysis." Studies on Korean Youth, National Youth Policy Institute, 29(1), pp. 145-177. 

  26. Park, J.H., and Lee, H.K. (2010). "The Accuracy Analysis of Data Mining Cost Prediction Methods by Cost Factors Classification." Journal of the Regional Association of Architectural Institute of Korea, Regional Association of Architectural Institute of Korea, 12(3), pp. 301-308. 

  27. Park, S.H., Kim, S.S., and Hwang H.S. (2011). Understanding and Utilization of Advanced SPSS, Hannarae. 

  28. Quan, Z., and Valdez, E.A. (2018). "Predictive Analytics of Insurance Claims using Multivariate Decision Trees." Dependence Modeling, De Gruyter Open Ltd. 6(1), pp. 377-407. 

  29. Sa, Y.B., Choi, S.U., Cho, W.C., and Lee, T.S. (2012). "Cost Analysis of Fall Accidents in Domestic Construction Industry." Journal of Korean Society of Societal Security, Korean Society of Disaster & Security, 5(1), pp. 1-6. 

  30. Son, Y., and Kim, H. (2012). "Forecasting Export & Import Container Cargoes using a Decision Tree Analysis." Journal of Korea Port Economic Association, Korea Port Economic Association, 28(4), pp. 193-207. 

  31. Song, Y.Y., Lu, Y. (2015). "Decision Tree Methods: Applications for Classification and Prediction." Shanghai Archives of Psychiatry, Editorial Board of Shanghai Archives of Psychiatry, 27(2), pp. 130-135. 

  32. Wang, C., Xinyi, Z., Minggang, W., Ming, K.L., and Pezhman, G. (2019). "Predictive Analytics of the Copper Spot Price by Utilizing Complex Network and Artificial Neural Network Techniques." Resources Policy, Elsevier, 63, 101414, pp. 1-17. 

  33. Yang, Y.K., and Kim, B.S. (2014). "An Analysis of Influential Factors and their Prioritization in Association with the Loss from Construction Disasters with a Focus on Uninsured Categories." Journal of the Korea Safety Management & Science, Korea Safety Management & Science, 16(3), pp. 23-34. 

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