Flexible Bayesian Ensemble Machine Learning Framework for Predicting Local Ozone Concentrations-Reference-Cited by-同舟云学术

Flexible Bayesian Ensemble Machine Learning Framework for Predicting Local Ozone Concentrations

Published:2022-03-21 Issue:7 Volume:56 Page:3871-3883
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Ren Xiang¹²^ORCID,Mi Zhongyuan¹³,Cai Ting¹,Nolte Christopher G.⁴,Georgopoulos Panos G.¹²³⁵^ORCID

Affiliation:

1. Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University, Piscataway, New Jersey 08854, United States

2. Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States

3. Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey 08901, United States

4. Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States

5. Department of Environmental and Occupational Health and Justice, Rutgers School of Public Health, Piscataway, New Jersey 08854, United States

Funder

National Institute of Environmental Health Sciences

National Center for Advancing Translational Sciences

New Jersey Department of Environmental Protection

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.1c04076

Reference54 articles.

1. USEPA CMAQ publications and peer review. https://www.epa.gov/cmaq/cmaq-publications-and-peer-review (accessed Oct 30, 2021).

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