The Canadian Optimized Statistical Smoke Exposure Model (Canossem): A Machine Learning Approach to Estimate National Daily Fine Particulate Matter (Pm2.5) Exposure-Reference-Cited by-同舟云学术

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The Canadian Optimized Statistical Smoke Exposure Model (Canossem): A Machine Learning Approach to Estimate National Daily Fine Particulate Matter (Pm2.5) Exposure

Published:2022 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

Paul Naman,Yao Jiayun,McLean Kathleen E.,Stieb Dave M.,Henderson Sarah B.

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference43 articles.

1. Weighted sampling without replacement;A Ben-Hamou;Brazilian Journal of Probability and Statistics,2018

2. Connecting smoke plumes to sources using Hazard Mapping System (HMS) smoke and fire location data over North America;S J Brey;Atmospheric Chemistry and Physics,2018

3. Predicting Daily Urban Fine Particulate Matter Concentrations Using a Random Forest Model;C Brokamp;Environmental Science and Technology,2018

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