Deep Ensemble Machine Learning Framework for the Estimation of PM2.5 Concentrations-Reference-Cited by-同舟云学术

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Deep Ensemble Machine Learning Framework for the Estimation of PM2.5 Concentrations

Published:2022-03 Issue:3 Volume:130 Page:
ISSN:0091-6765
Container-title:Environmental Health Perspectives
language:en
Short-container-title:Environ Health Perspect

Author:

Yu Wenhua¹^ORCID,Li Shanshan¹,Ye Tingting¹,Xu Rongbin¹,Song Jiangning²^ORCID,Guo Yuming¹

Affiliation:

1. Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

2. Monash Biomedicine Discovery Institute, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia

Publisher

Environmental Health Perspectives

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference84 articles.

1. Alpaydin E. 2020. Introduction to Machine Learning. Cambridge, MA: MIT Press.

2. Allocating optimum sites for air quality monitoring stations using GIS suitability analysis

3. An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting

4. Present and future Köppen-Geiger climate classification maps at 1-km resolution

5. DALEX: explainers for complex predictive models in R;Biecek P;J Mach Learn Res,2018

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