Development of a predictive emissions model using a gradient boosting machine learning method-Reference-Cited by-同舟云学术

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Development of a predictive emissions model using a gradient boosting machine learning method

Published:2020-11 Issue: Volume:20 Page:101028
ISSN:2352-1864
Container-title:Environmental Technology & Innovation
language:en
Short-container-title:Environmental Technology & Innovation

Author:

Si Minxing,Du Ke

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Plant Science,Soil Science,General Environmental Science

Reference44 articles.

1. Predictive emission monitoring systems the new approach for monitoring emissions from industry [www document];ABB S.p.A.,2014

2. CEMS Alternatives – A different way;Bivens,2017

3. Bivens, T., 2019. Arkansas Electric Cooperative Corporation. Little Rock, Arkansas. Personal communication.

4. Impact of nitrogen oxides on the environment and human health: Mn-based materials for the NO x abatement;Boningari;Curr. Opin. Chem. Eng.,2016

5. Predictive emission monitoring (PEM) systems development and implementation;Botros,2011

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