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연구논문

산업재해의 최적 예측모형을 위한 근사모형에 관한 연구

원문정보

A Study on Approximation Model for Optimal Predicting Model of Industrial Accidents

임영문, 유창현

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare algorithms for data analysis of industrial accidents and this paper provides an optimal predicting model of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. Also, this paper provides an approximation model for an optimal predicting model based on NN. The approximation model provided in this study can be utilized for easy interpretation of data analysis using NN. This study uses selected ten independent variables to group injured people according to a dependent variable in a way that reduces variation. In order to find an optimal predicting model among 5 algorithms, a retrospective analysis was performed in 67,278 subjects. The sample for this work chosen from data related to industrial accidents during three years () in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.

목차

Abstract
 1. 서론
 2. 연구내용 및 방법
  2.1 연구 자료
  2.2 분석방법
 3. 분석 결과
  3.1 변수 선택
  3.2 모델별 결과 비교
  3.3 의사결정나무를 이용한 신경망 근사모형 분석
 5. 결론 및 추후연구
 6. 참고문헌

저자정보

  • 임영문 Leem Young Moon. 강릉대학교 산업공학과 교수
  • 유창현 Ryu Chang Hyun. 강릉대학교 산업공학과 석사과정

참고문헌

자료제공 : 네이버학술정보

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