Predicting PM2.5 in Well-Mixed Indoor Air for a Large Office Building Using Regression and Artificial Neural Network Models
Author:
Affiliation:
1. Division of Computing and Software Systems, University of Washington Bothell, Bothell, Washington 98011, United States
2. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
Funder
National Science Foundation
Publisher
American Chemical Society (ACS)
Subject
Environmental Chemistry,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.est.0c02549
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