Predicting bioavailability of potentially toxic elements (PTEs) in sediment using various machine learning (ML) models: A case study in Mahabad Dam and River-Iran-Reference-Cited by-同舟云学术

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Predicting bioavailability of potentially toxic elements (PTEs) in sediment using various machine learning (ML) models: A case study in Mahabad Dam and River-Iran

Published:2024-08 Issue: Volume:366 Page:121788
ISSN:0301-4797
Container-title:Journal of Environmental Management
language:en
Short-container-title:Journal of Environmental Management

Author:

Rezaei Fateme,Rastegari Mehr Meisam^ORCID,Shakeri Ata,Sacchi Elisa^ORCID,Borna Keivan^ORCID,Lahijani Omid

Funder

Iran Water Resources Management Company

Kharazmi University

Publisher

Elsevier BV

Reference105 articles.

1. Artificial intelligence applications in solid waste management: a systematic research review;Abdallah;Waste Manag.,2020

2. Energy-efficient edge based real-time healthcare support system;Abirami,2020

3. Salinity increases mobility of heavy metals in soils;Acosta;Chemosphere,2011

4. Heavy metal enrichment and potential ecological risks from different solid mine wastes at a mine site in Ghana;Akoto;Environmental Advances,2021

5. Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques;Alejo;Environ. Sci. Pollut. Control Ser.,2018

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