Prediction of Hourly PM2.5 and PM10 Concentrations in Chongqing City in China Based on Artificial Neural Network
Abstract Accurate prediction of air pollution is a difficult problem to be solved in atmospheric environment research. An Artificial Neural Network (ANN) is exploited to predict hourly PM2.5 and PM10 concentrations in Chongqing City. We take PM2.5 (PM10), time and meteorological elements as the inpu...
Saved in:
Main Authors: | Qingchun Guo, Zhenfang He, Zhaosheng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2023-03-01
|
Series: | Aerosol and Air Quality Research |
Subjects: | |
Online Access: | https://doi.org/10.4209/aaqr.220448 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Measurement of PM2.5 and PM10 Concentrations in Nakhodka City with a Network of Automatic Monitoring Stations
by: Aleksei Kholodov, et al.
Published: (2022-07-01) -
Assessment of Machine Learning Algorithms in Short-term Forecasting of PM10 and PM2.5 Concentrations in Selected Polish Agglomerations
by: Bartosz Czernecki, et al.
Published: (2021-03-01) -
Estimation of PM10 and PM2.5 Using Backscatter Coefficient of Ceilometer and Machine Learning
by: Bu-Yo Kim, et al.
Published: (2023-10-01) -
Field Tests of Indoor Air Cleaners for Removal of PM2.5 and PM10 in Elementary School Classrooms in Seoul, Korea
by: Bangwoo Han, et al.
Published: (2022-03-01) -
Influence of Secondary Inorganic Aerosol on the Concentrations of PM2.5 and PM0.1 during Air Pollution Episodes in Hanoi, Vietnam
by: Nguyen-Quoc Dat, et al.
Published: (2024-02-01)