원문정보
Estimation and Classification of COVID-19 through Climate Change : Focusing on Weather Data since 2018
초록
영어
The causes of climate change are natural and artificial. Natural causes include changes in temperature and sunspot activities caused by changes in solar radiation due to large-scale volcanic activities, while artificial causes include increased greenhouse gas concentrations and land use changes. Studies have shown that excessive carbon use among artificial causes has accelerated global warming. Climate change is rapidly under way because of this. Due to climate change, the frequency and cycle of infectious disease viruses are greater and faster than before. Currently, the world is suffering greatly from coronavirus infection-19 (COVID-19). Korea is no exception. The first confirmed case occurred on January 20, 2020, and the number of infected people has steadily increased due to several waves since then, and many confirmed cases are occurring in 2021. In this study, we conduct a study on climate change before and after COVID-19 using weather data from Korea to determine whether climate change affects infectious disease viruses through logistic regression analysis. Based on this, we want to classify before and after COVID-19 through a logistic regression model to see how much classification rate we have. In addition, we compare monthly classification rates to see if there are seasonal classification differences.
목차
1. Introduction
2. Data Information
2.1. 평균기온 추이 및 기술통계량
2.2. 평균풍속 추이 및 기술통계량
2.3. 평균상대습도 추이 및 기술통계량
2.4. 평균현지기압 추이 및 기술통계량
2.5. 합계일사량 추이 및 기술통계량
2.6. 평균지면온도 추이 및 기술통계량
2.7. 미세먼지 농도 추이 및 기술통계량
3. Analysis
3.1. 상관분석 결과
3.2. 로지스틱 회귀분석 결과
3.3. 분류율 결과
4. Conclusion
Acknowlegments
References