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대구광역시 어린이 및 노인 보행자의 교통사고 영향 요인 분석
황영은(Yeongeun Hwang),윤상후(Sanghoo Yoon) 한국자료분석학회 2023 Journal of the Korean Data Analysis Society Vol.25 No.3
보행자 교통사고는 보행자와 운행 중인 차량 간 발생한 충돌사고로 도로 및 주변 환경 등에 영향을 받는다. 이 연구에서는 2014년 1월 1일부터 2019년 12월 31일까지 대구광역시에서 발생한 차대사람 교통사고 자료와 2차 자료를 수집하여 보행자교통사고에 영향을 미치는 요인을 분석하였다. 보행자는 어린이, 일반인, 노인으로 구분한 후 일반인을 대조집단으로 어린이와 노인을 시험집단으로 간주하여 교통약자(어린이, 노인) 보행자 교통사고 요인을 파악하였다. 교통사고 발생 빈도가 적은 어린이와 노인의 자료 불균형 문제를 해결하기 위해 SMOTE 알고리즘을이용하였다. 분석에 고려된 연구모형은 다항 로지스틱 회귀모형, 랜덤포레스트, Gradient Boosting Machine(GBM), XGBoost이다. 분석 결과 앙상블 기반의 의사결정나무를 사용한 랜덤포레스트, XGBoost, GBM의 분류성능이 다항 로지스틱 회귀모형에 비해 우수하였다. 대구광역시에서는 어린이 보행자 교통사고가 일반인 보행자 교통사고에 비해 맑은 날 13시~20시 공단 밀집 지역에서 주로 발생하였다. 노인 보행자 교통사고는 일반인 보행자 교통사고에 비해 맑은 날 9시~12시 전통시장을 비롯한 도심지역의 교차로에서 주로 발생하였다. 어린이와 노인 교통사고와 연관된 요인은 교육기관 수, 차량등록 수, 강수 여부, 학원 수, 공원 수, 노인시설 수 순서로 높게 도출되었다. A pedestrian traffic accident is a collision between a pedestrian and a moving vehicle that occurs within the surrounding road environment. The traffic accident data and secondary data from Daegu were collected and utilized between January 2014 and December 2019. The traffic accident data was divided into children, ordinary, and seniors according to the age of pedestrians. A classification model was applied to determine the ranking of the influencing factors. SMOTE was used to address the imbalance in traffic accidents among children and seniors compared to ordinary. The multinomial logistic regression model (MLR), random forest (RF), GBM, and XGBoost were considered classification models. The classification performance of RF, XGBoost, and GBM using ensemble-based decision trees was superior to that of the MLR. The results showed that the important variables for explaining pedestrian traffic accidents were as follows: children pedestrians suffered between 13:00 and 20:00 on sunny days in densely populated industrial complex areas. On the other hand, senior pedestrians faced higher risks of vehicle accidents between 9:00 and 12:00 on sunny days, mainly at intersections in downtown areas with traditional markets. As for the important influencing factors derived from the research, the number of educational institutions, the number of vehicle registrations, precipitation, the number of academies, the number of parks, and the number of facilities for the elderly ranked high accordingly.
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밭작물 농업기상을 위한 수치형 산림입지토양도 활용성 평가
강다영 ( Dayoung Kang ),황영은 ( Yeongeun Hwang ),윤상후 ( Sanghoo Yoon ) 한국농림기상학회 2021 한국농림기상학회지 Vol.23 No.1
Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 1 2 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.
KCI
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