Unveiling the drives behind tetracycline adsorption capacity with biochar through machine learning

This study aimed to develop a robust predictive model for tetracycline (TC) adsorption onto biochar (BC) by employing machine learning techniques to investigate the underlying driving factors. Four machine learning algorithms, namely Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtrem...

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Detalles Bibliográficos
Autores principales: Zhang, Pengyan, Liu, Chong, Lao, Dongqing, Nguyen, Xuan Cuong, Paramasivan, Balasubramanian, Qian, Xiaoyan, Inyinbor, Adejumoke Abosede, Hu, Xuefei, You, Yongjun, Li, Fayong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352365/
https://www.ncbi.nlm.nih.gov/pubmed/37460544
http://dx.doi.org/10.1038/s41598-023-38579-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352365/
https://www.ncbi.nlm.nih.gov/pubmed/37460544
http://dx.doi.org/10.1038/s41598-023-38579-8

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