Impact of the weighted loss function on the innovative CMAQ-CNN PM2.5 forecasting model

Yi Ju Lee, Fang Yi Cheng, Chih Yung Feng, Zhih Min Yang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Developing an accurate air quality forecasting model with a lead time longer than 72 hours is important for predicting hazardous pollution events. An air quality forecasting system (AQF) conducted with the WRF-CMAQ numerical model has been developed. This study used the predicted PM2.5 from AQF, observed PM2.5, longitude, latitude, the land use index of the corresponding grid, and indexes of synoptic weather patterns to develop a forecasting model through the CNN algorithm to predict 72 hours of PM2.5 concentrations at 75 surface air quality monitoring sites. The training dataset was from October 2019 to September 2021, and the data from October 2021 to September 2022 was divided into validation and test datasets in order of date. Since the PM2.5 varies in a wide range, the weighted loss function was applied to improve the model performance. In general, the CMAQ-CNN models developed by this study show better performance than the AQF, especially during high pollution events when the CMAQ-CNN model utilizes the weighted loss function.

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主出版物標題2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
發行者Institute of Electrical and Electronics Engineers Inc.
頁面2261-2266
頁數6
ISBN(電子)9798350300673
DOIs
出版狀態已出版 - 2023
事件2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023 - Taipei, Taiwan
持續時間: 31 10月 20233 11月 2023

出版系列

名字2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023

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???event.eventtypes.event.conference???2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
國家/地區Taiwan
城市Taipei
期間31/10/233/11/23

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