PM10 and PM2.5 real-time prediction models using an interpolated convolutional neural network
Abstract In this paper, we propose a real-time prediction model that can respond to particulate matters (PM) in the air, which are an indication of poor air quality. The model applies interpolation to air quality and weather data and then uses a Convolutional Neural Network (CNN) to predict PM conce...
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Auteurs principaux: | Sangwon Chae, Joonhyeok Shin, Sungjun Kwon, Sangmok Lee, Sungwon Kang, Donghyun Lee |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/3830b8fdb2bc4eb888ec0b6ae92c3406 |
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