Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea
Amidst recent industrialization in South Korea, Seoul has experienced high levels of air pollution, an issue that is magnified due to a lack of effective air pollution prediction techniques. In this study, the Prophet forecasting model (PFM) was used to predict both short-term and long-term air poll...
Main Authors: | Justin Shen, Davesh Valagolam, Serena McCalla |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2020-09-01
|
Series: | PeerJ |
Subjects: | |
Online Access: | https://peerj.com/articles/9961.pdf |
Similar Items
-
Status of Ambient PM2.5 Pollution in the Seoul Megacity (2020)
by: Jung-Hoon Uhm, et al.
Published: (2021-06-01) -
Urban settlement design, Seoul, Korea : a comparative study for low-income housing
by: Je, Hae-Seong
Published: (2012) -
Aerobiological study of pollen and mold in Seoul, Korea
by: Jae-Won Oh, et al.
Published: (1998-01-01) -
An analysis of the aspects attracting medical tourists : a case study in Seoul, South Korea
by: Jung, Da ok
Published: (2012) -
Social cohesiveness and the physical environment of Korean public housing communities in Seoul
by: Seo, Bo-Kyong, et al.
Published: (2014)