Journal of the Korean Society of Safety (한국안전학회지)

The Korean Society of Safety (한국안전학회)
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Construction Safety and Health Management Cost Prediction Model using Support Vector Machine

서포트 벡터 머신을 이용한 건설업 안전보건관리비 예측 모델

  • Shin, Sung Woo (Department of Safety Engineering, Pukyong National University)
  • Received : 2017.02.03
  • Accepted : 2017.02.10
  • Published : 2017.02.28
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Abstract

The aim of this study is to develop construction safety and health management cost prediction model using support vector machine (SVM). To this end, theoretical concept of SVM is investigated to formulate the cost prediction model. Input and output variables have been selected by analyzing the balancing accounts for the completed construction project. In order to train and validate the proposed prediction model, 150 data sets have been gathered from field. Effects of SVM parameters on prediction accuracy are analyzed and from which the optimal parameter values have been determined. The prediction performance tests are conducted to confirm the applicability of the proposed model. Based on the results, it is concluded that the proposed SVM model can effectively be used to predict the construction safety and health management cost.

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References

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