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Study on Accident Prediction Models in Urban Railway Casualty Accidents Using Logistic Regression Analysis Model
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로지스틱회귀분석 모델을 활용한 도시철도 사상사고 사고예측모형 개발에 대한 연구

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Type
Academic journal
Author
Soo-Bong. Jin (Seoul National University of Science and Technology) Jong-Woo. Lee (Seoul National University of Science and Technology)
Journal
The Korean Society For Railway Journal of the Korean Society for Railway Vol.20 No.4 (Wn.101) KCI Accredited Journals SCOPUS
Published
2017.8
Pages
482 - 490 (9page)

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Study on Accident Prediction Models in Urban Railway Casualty Accidents Using Logistic Regression Analysis Model
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Abstract· Keywords

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This study is a railway accident investigation statistic study with the purpose of prediction and classification of accident severity. Linear regression models have some difficulties in classifying accident severity, but a logistic regression model can be used to overcome the weaknesses of linear regression models. The logistic regression model is applied to escalator (E/S) accidents in all stations on 5~8 lines of the Seoul Metro, using data mining techniques such as logistic regression analysis. The forecasting variables of E/S accidents in urban railway stations are considered, such as passenger age, drinking, overall situation, behavior, and handrail grip. In the overall accuracy analysis, the logistic regression accuracy is explained 76.7%. According to the results of this analysis, it has been confirmed that the accuracy and the level of significance of the logistic regression analysis make it a useful data mining technique to establish an accident severity prediction model for urban railway casualty accidents.

Contents

Abstract
초록
1. 연구배경 및 목적
2. 철도사고 예측모델 선행연구
3. 에스컬레이터 전도사고의 로지스틱회귀분석 모델
4. 사고예측 모형 및 적합성 검증
5. 결론
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UCI(KEPA) : I410-ECN-0101-2018-557-001276643