공간분석·데이터마이닝 융합방법론을 통한 산업안전 취약지 등급화 방안

서지정보

ㆍ발행기관 : 한국산업경영시스템학회 ㆍ수록지정보 : 산업경영시스템학회지 / 40권 / 4호
ㆍ저자명 : 고경석, 양재경

목차

1. 서 론
2. 연구방법
3. 공간분석 및 데이터마이닝
3.1 데이터목록
3.2 데이터 전처리 및 융합
3.3 탐색적 분석 및 공간 시각화
3.4 주성분 분석
3.5 지리적 가중회귀분석
3.6 CART-부스팅 분석
3.7 위험도 등급화 및 공간조인
4. 결 론
References

영어 초록

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It’s five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class’s average deviation from the class mean, while maximizing each class’s deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.

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