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학술논문한국설비안전학회지2018.03 발행KCI 피인용 7

서비스 산업에서 동적 모형을 고려한 업무상 사고 사망과재해율 예측

Forecasting of the Fatal Accident and Accident Rate Considering Dynamic Model in the Service Industry

강영식(세명대학교)

23권 1호, 39~48쪽

초록

Occupational accident rate in Korea has occurred most frequently in the service industry. Accordingly, forecasting of the occupational accident rate and fatal accident rate is very important in order to prevent the industrial accidents in the service industry systematically. This paper considers not only static methods but also dynamic method among time series analysis methods. Therefore, 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), and kalman filtering model (KFM) with existing accident data in service industry. In this paper, MFC (Microsoft Foundation Class) software of Visual Studio 2008 was used to predict the occupational accident rate and the fatal accident rate. The minimum value for minimizing SSE in the service industry was found in 0.2714 and 0.0233 in the occupational accident rate and fatal accident rate, respectively. Accordingly, ARIMA model in service industry are ideally applied in the accident rate and fatal accident rate.

Abstract

Occupational accident rate in Korea has occurred most frequently in the service industry. Accordingly, forecasting of the occupational accident rate and fatal accident rate is very important in order to prevent the industrial accidents in the service industry systematically. This paper considers not only static methods but also dynamic method among time series analysis methods. Therefore, 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), and kalman filtering model (KFM) with existing accident data in service industry. In this paper, MFC (Microsoft Foundation Class) software of Visual Studio 2008 was used to predict the occupational accident rate and the fatal accident rate. The minimum value for minimizing SSE in the service industry was found in 0.2714 and 0.0233 in the occupational accident rate and fatal accident rate, respectively. Accordingly, ARIMA model in service industry are ideally applied in the accident rate and fatal accident rate.

발행기관:
한국설비안전학회
분류:
설비관리

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서비스 산업에서 동적 모형을 고려한 업무상 사고 사망과재해율 예측 | 한국설비안전학회지 2018 | AskLaw | 애스크로 AI