Optimized neural network for daily-scale ozone prediction based on transfer learning-Reference-Cited by-同舟云学术

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Optimized neural network for daily-scale ozone prediction based on transfer learning

Published:2022-06 Issue: Volume:827 Page:154279
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Ma Wei,Yuan Zibing,Lau Alexis K.H.,Wang Long,Liao Chenghao,Zhang Yongbo

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference45 articles.

1. Sensitivity of meteorological skill to selection of WRF-chem physical parameterizations and impact on ozone prediction during the Lake Michigan ozone study (LMOS);Abdi-Oskouei;J. Geophys. Res.-Atmos.,2020

2. Prediction of ozone concentration in ambient air using multilinear regression and the artificial neural networks methods;Arsic;Ozone Sci. Eng.,2020

3. Prediction of daily ozone concentration maxima in the urban atmosphere;Barrero;Chemom. Intell. Lab. Syst.,2006

4. Artificial neural networks for estimating regional arsenic concentrations in a Blackfoot disease area in Taiwan;Chang;J. Hydrol.,2010

5. Understanding the causal influence of major meteorological factors on ground ozone concentrations across China;Chen;J. Clean. Prod.,2020

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