• 한국안전학회지
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• 제29권1호
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• pp.54-58
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• 2014

This study deals with the accidents of circular intersections in Korea. The goal is to develop the accident models for 94 circular intersections. In pursuing the above, this study gives particular attentions to collecting the data of geometric structure and accidents, and comparatively analyzing such the models as Poisson and NB regression and multiple regression model using SPSS 17.0 and LIMDEP 3.0. The main results are as follows. First, the negative binomial model among various models was analyzed to be the most appropriate. Second, 3 independent variables was adopted in the model, and these variables was analyzed to have a positive relation to the accident rate. Finally, the reduced width of circulatory roadway, removal of the parking lot within circulatory roadway and appropriate levels of approach lane were required to improve the safety of circular intersection.

• 한국안전학회지
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• 제29권3호
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• pp.107-113
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• 2014

The goal of this study is to develop the accident models of motorcycle at roundabouts. In the pursuing the above, this study gives particular attentions to developing the appropriate models using ZAM. The main results are as follows. First, the evaluation of various developed models by the Vuong statistic and over-dispersion parameter shows that ZINB is analyzed to be optimal among Poisson, NB, ZIP(zero-inflated Poisson) and ZINB regression models. Second, the traffic volume, width of central island and width of approach are evaluated to be important variables to the accidents. Finally, the common variables that affect to the accident are selected to be traffic volume and width of approach. This study might be expected to give some implications to the accident research on the roundabout by motorcycle.

• 한국도로학회논문집
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• 제12권2호
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• pp.43-49
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• 2010

본 연구는 청주시의 가로구간 교통사고를 다루고 있다. 연구의 목적은 가로구간의 사고모형을 개발하는 데 있다. 이를 위해서 이 연구에서는 전체 322개 세부구간으로 분리된 간선도로의 사고 자료를 이용하여 ZAM 모형을 개발하는데 중점을 두고 있다. ZAM 모형의 일종인 ZIP(zero inflated Poisson model)과 ZINB(zero inflated negative binomial model)를 중심으로 분석한 연구의 주요결과는 다음과 같다. 첫째, 모형의 적합성을 결정하는 Vuong 통계 값과 과분산계수 ${\alpha}$의 t 통계 값을 바탕으로 개발된 다양한 모형을 평가한 결과, 포아송, 음이항, ZIP 및 ZINB 회귀모형 중 ZINB 모형이 최적인 것으로 나타난다. 둘째, ZINB 모형은 t, ${\rho}$ 및 ${\rho}^2$값 (0.63)의 관점에서 보면, 다른 모형에 비해서 통계적으로 매우 의미 있는 모형으로 평가된다. 마지막으로, 개발된 ZINB 모형의 사고 요인은 교통량, 진출입구 수 그리고 중앙분리대 길이로 분석된다. 교통량과 진출입구 수는 사고발생에 '+'요인, 그리고 중앙분리대 길이는 '-'요인으로 평가된다.

• Genomics & Informatics
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• 제19권1호
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.