기상환경데이터와 머신러닝을 활용한 미세먼지농도 예측 모델

• 영문명: An Estimation Model of Fine Dust Concentration Using Meteorological Environment Data and Machine Learning
• 발행기관: 한국IT서비스학회
• 저자명: 임준묵(Joon-Mook Lim)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제18권 제1호, 173~186쪽, 전체 14쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2019.03.30

영문 초록

Recently, as the amount of fine dust has risen rapidly, our interest is increasing day by day. It is virtually impossible to remove fine dust. However, it is best to predict the concentration of fine dust and minimize exposure to it. In this study, we developed a mathematical model that can predict the concentration of fine dust using various information related to the weather and air quality, which is provided in real time in Air Korea (http://www.airkorea.or.kr/) and Weather Data Open Portal (https://data.kma.go.kr/). In the mathematical model, various domestic seasonal variables and atmospheric state variables are extracted by multiple regression analysis. The parameters that have significant influence on the fine dust concentration are extracted, and using ANN (Artificial　Neural　Network) and SVM (Support Vector Machine), which are machine learning techniques, we proposed a prediction model. The proposed model can verify its effectiveness by using past dust and weather big data.

목차

1. 서 론

2. 미세먼지농도 예측 기존연구 및예측모델 제안

3. 기상환경데이터와 미세먼지의 빅데이터 수집 및 처리

4. 머신러닝기법을 활용한 미세먼지의 예측모델

5. 결 론

키워드

Fine Dust Machine Learning Weather Data Bigdata