The application of transfer machine learning to predict and impute missing sulphate levels in different Acid Mine Drainage treatment plants-Reference-Cited by-同舟云学术

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The application of transfer machine learning to predict and impute missing sulphate levels in different Acid Mine Drainage treatment plants

Published:2024-12 Issue: Volume:2 Page:100029
ISSN:2950-2632
Container-title:Cleaner Water
language:en
Short-container-title:Cleaner Water

Author:

Hasrod Taskeen^ORCID,Nuapia Yannick B.,Tutu Hlanganani^ORCID

Funder

University of the Witwatersrand, Johannesburg

Publisher

Elsevier BV

Reference37 articles.

1. 3.2 - Identifying Outliers: IQR Method [WWW Document], 2023. URL 〈https://online.stat.psu.edu/stat200/lesson/3/3.2〉 (accessed 3.29.24).

2. Acid Mine Drainage (AMD): causes, treatment and case studies;Akcil;J. Clean. Prod.,2006

3. Simple methods for quantitative determination of sulphate ions from aqueous media with industrial applications;Anechiţei;Bull. Polytech. Inst. Jassy,2019

4. Clay and non-clay minerals in the pharmaceutical and cosmetic industries Part II. Active ingredients;Carretero;Appl. Clay Sci.,2010

5. Processes controlling metal ion attenuation in acid mine drainage streams;Chapman;Geochim. Ef. Cosmwhimica Ado,1983

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