Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model-Reference-Cited by-同舟云学术

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Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model

Published:2021-09 Issue: Volume:261 Page:118599
ISSN:1352-2310
Container-title:Atmospheric Environment
language:en
Short-container-title:Atmospheric Environment

Author:

Gao Shuang,Bai Zhipeng,Liang Shuang,Yu Hao,Chen Li,Sun Yanling,Mao Jian,Zhang Hui,Ma Zhenxing,Azzi Merched,Zhao Hong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Atmospheric Science,General Environmental Science

Reference69 articles.

1. Air quality forecasting using artificial neural networks with real time dynamic error correction in highly polluted regions;Agarwal;Sci. Total Environ.,2020

2. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5;Ausati;Atmos. Environ.,2016

3. Analysis of surface ozone using a recurrent neural network;Biancofiore;Sci. Total Environ.,2015

4. Recursive neural network model for analysis and forecast of PM10 and PM2.5;Biancofiore;Atmos. Pollut. Res.,2017

5. Dominant role of emission reduction in PM2.5: air quality improvement in Beijing during 2013-2017: a model-based decomposition analysis;Cheng;Atmos. Chem. Phys.,2019

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