Forecasting PM2.5 levels in Santiago de Chile using deep learning neural networks-Reference-Cited by-同舟云学术

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Forecasting PM2.5 levels in Santiago de Chile using deep learning neural networks

Published:2021-07 Issue: Volume:38 Page:100906
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Menares Camilo,Perez Patricio,Parraguez Santiago,Fleming Zoë L.

Funder

Universidad de Santiago de Chile

Departamento de Investigaciones Científicas y Tecnológicas, Universidad de Santiago de Chile

Publisher

Elsevier BV

Subject

Atmospheric Science,Urban Studies,Environmental Science (miscellaneous),Geography, Planning and Development

Reference54 articles.

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

2. Procedures for estimation of modelling uncertainty in air quality assessment;Borrego;Environ. Int.,2008

3. Selection of key features for PM2.5 prediction using a wavelet model and RBF-LSTM;Chen;Appl. Intell.,2021

4. Lag order and critical values of the augmented dickey–fuller test;Cheung;J. Bus. Econ. Stat.,1995

5. Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: a tutorial using simulations and empirical data;de Winter;Psychol. Methods,2016

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