A Novel Domain Knowledge-Informed Machine Learning Approach for Modeling Solid Waste Management Systems-Reference-Cited by-同舟云学术

A Novel Domain Knowledge-Informed Machine Learning Approach for Modeling Solid Waste Management Systems

Published:2023-09-30 Issue:46 Volume:57 Page:18215-18224
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

He Rui¹^ORCID,Small Mitchell J.¹,Scott Ian J.²,Olarinre Motolani³,Sandoval-Reyes Mexitli⁴,Ferrão Paulo⁴

Affiliation:

1. Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States

2. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisbon, Portugal

3. Department of Machine Learning, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States

4. IN+ Center for Innovation, Technology and Policy Research, LARSyS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

Funder

Carnegie Mellon University

Minist??rio da Educa????o e Ci??ncia

Carnegie Mellon Portugal

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c04214

Reference55 articles.

1. What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050

2. Sustainable waste management systems

3. From linear to circular integrated waste management systems: A review of methodological approaches

4. Solid waste management: Scope and the challenge of sustainability

5. The development of an environmental Decision Support System for municipal solid waste management

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