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KCI 후보
임업에서 정적 모형과 동적 모형을 적용한 업무상사고 사망과 재해율 예측
Forecasting of the Fatal Accident and Accident Rate by Static and Dynamic Method in the Forestry
강영식 ( Young-sig Kang )
UCI I410-ECN-0102-2019-500-001453076

Occupational accident rate in Korea has occurred most frequently in the service industry, manufacturing industry, and construction industry. However, forestry, agriculture, and fishing are in a blind spot in policies of occupational safety and health because they are usually under 50 workers. So these industries are very important in order to prevent of industrial accidents because of poor safety management. Above all, accurate prediction of the occupational accident rate and fatal accident rate in the forestry is required to prevent the occupational accidents systematically and continuously. Therefore, this paper proposes very efficient policies for prevention of industrial accidents with these prediction results in the forestry. Also, this paper describes the optimal occupational accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM) by static method, and, kalman filtering model (KFM) by dynamic method with existing accident data in forestry. In this paper, microsoft foundation class (MFC) software of Visual Studio 2008 was used to minimize SSE of the occupational accident rate and the fatal accident rate. The minimum value of SSE in the forestry was found in 2.8822 and 6.0055 in the occupational accident rate and fatal accident rate, respectively. Accordingly, ARIMA model in the forestry are ideally applied in the accident rate and fatal accident rate. Finally, this paper provides very efficient strategic method in order to prevent the accident of forestry through the trend of determined prediction model and analysis of accident data.

1. 서 론
2. 연구방법 및 재해율 예측 모형
3. 사례연구
4. 결 론
Acknowledgement
References
[자료제공 : 네이버학술정보]
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