The application of machine learning methods for prediction of metal sorption onto biochars
10.1016/j.jhazmat.2019.06.004
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2021
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sg-nus-scholar.10635-1911682024-03-26T08:51:21Z The application of machine learning methods for prediction of metal sorption onto biochars ZHU XINZHE WANG XIAONAN YONG SIK OK CHEMICAL & BIOMOLECULAR ENGINEERING Pyrolysis Charcoal Sorption model Machine learning Artificial intelligence 10.1016/j.jhazmat.2019.06.004 Journal of Hazardous Materials 378 2021-05-11T03:11:26Z 2021-05-11T03:11:26Z 2019-06-03 Article ZHU XINZHE, WANG XIAONAN, YONG SIK OK (2019-06-03). The application of machine learning methods for prediction of metal sorption onto biochars. Journal of Hazardous Materials 378. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jhazmat.2019.06.004 0304-3894 https://scholarbank.nus.edu.sg/handle/10635/191168 Elsevier |
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Pyrolysis Charcoal Sorption model Machine learning Artificial intelligence |
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Pyrolysis Charcoal Sorption model Machine learning Artificial intelligence ZHU XINZHE WANG XIAONAN YONG SIK OK The application of machine learning methods for prediction of metal sorption onto biochars |
description |
10.1016/j.jhazmat.2019.06.004 |
author2 |
CHEMICAL & BIOMOLECULAR ENGINEERING |
author_facet |
CHEMICAL & BIOMOLECULAR ENGINEERING ZHU XINZHE WANG XIAONAN YONG SIK OK |
format |
Article |
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ZHU XINZHE WANG XIAONAN YONG SIK OK |
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ZHU XINZHE |
title |
The application of machine learning methods for prediction of metal sorption onto biochars |
title_short |
The application of machine learning methods for prediction of metal sorption onto biochars |
title_full |
The application of machine learning methods for prediction of metal sorption onto biochars |
title_fullStr |
The application of machine learning methods for prediction of metal sorption onto biochars |
title_full_unstemmed |
The application of machine learning methods for prediction of metal sorption onto biochars |
title_sort |
application of machine learning methods for prediction of metal sorption onto biochars |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://scholarbank.nus.edu.sg/handle/10635/191168 |
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1795301439643320320 |