Analysis of Tropospheric Ozone by Artificial Neural Network Approach in Beijing

ISSN Print: 2327-4336
ISSN Online: 2327-4344
www.scirp.net/journal/gep
E-mail: [email protected]

Citations

"Analysis of Tropospheric Ozone by Artificial Neural Network Approach in Beijing"
written by Muhammad Azher Hassan, Zhaomin Dong,
published by Journal of Geoscience and Environment Protection, Vol.6 No.11, 2018

has been cited by the following article(s):

[1]	A Comparative Study of Deep Learning Models on Tropospheric Ozone Forecasting Using Feature Engineering Approach
	Atmosphere, 2023

[2]	Assessment of meteorological and air quality drivers of elevated ambient ozone in Beijing via machine learning approach
	… Science and Pollution …, 2023

[3]	Prediction of air quality using vertical atmospheric condition and developing hybrid models
	Advances in Space Research, 2023

[4]	A Generic Model to Estimate Ozone Concentration from Landsat 8 Satellite Data Based on Machine Learning Technique
	2021

[5]	Air quality assessment and forecasting using neural network model
	2021

[6]	Connectionist modelling for anthropogenic greenhouse gases (GHG) emissions in urban environments.
	Applied Ecology & …, 2020

[1]	Prediction of air quality using vertical atmospheric condition and developing hybrid models Advances in Space Research, 2023 DOI:10.1016/j.asr.2023.04.020

[2]	Assessment of meteorological and air quality drivers of elevated ambient ozone in Beijing via machine learning approach Environmental Science and Pollution Research, 2023 DOI:10.1007/s11356-023-29665-5

[3]	A Generic Model to Estimate Ozone Concentration From Landsat 8 Satellite Data Based on Machine Learning Technique IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 DOI:10.1109/JSTARS.2021.3101206

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