Machine learning insights in predicting heavy metals interaction with biochar

被引：0
|
作者：
Xin Wei
Yang Liu
Lin Shen
Zhanhui Lu
Yuejie Ai
Xiangke Wang
机构：
[1] North China Electric Power University,School of Control and Computer Engineering
[2] North China Electric Power University,School of Mathematics and Physics
[3] North China Electric Power University,MOE Key Laboratory of Resources and Environmental Systems Optimization, College of Environment and Chemical Engineering
[4] Beijing Normal University,Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education, College of Chemistry
来源：
Biochar | / 6卷
关键词：
Biochar; Heavy metals; Interaction mechanism; Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A high growth rate of studies on the application of machine learning (ML) in biochar in recent years.ML interpretability of heavy metals (HMs) interaction mechanisms with biochar is explicated emphatically.Challenges and perspectives of ML application in the removal of HMs by biochar.Combining an advanced machine learning technique to achieve better predicted performance.
引用
收藏
相关论文
共 50 条
  • [31] Interaction of pristine and mineral engineered biochar with microbial community in attenuating the heavy metals toxicity: A review
    Batool, Masooma
    Khan, Waqas-ud-Din
    Hamid, Yasir
    Farooq, Muhammad Ansar
    Naeem, Muhammad Asif
    Nadeem, Faisal
    APPLIED SOIL ECOLOGY, 2022, 175
  • [32] Machine Learning Insights: Predicting Hepatic Encephalopathy After TIPS Placement
    Okan İnce
    Hakan Önder
    Mehmet Gençtürk
    Jafar Golzarian
    Shamar Young
    CardioVascular and Interventional Radiology, 2023, 46 : 1715 - 1725
  • [33] Addressing data handling shortcomings in machine learning studies on biochar for heavy metal remediation
    Cahyana, Destika
    Jang, Ho Jun
    JOURNAL OF HAZARDOUS MATERIALS, 2025, 491
  • [34] Machine Learning Insights: Predicting Hepatic Encephalopathy After TIPS Placement
    Ince, Okan
    Onder, Hakan
    Genctuerk, Mehmet
    Golzarian, Jafar
    Young, Shamar
    CARDIOVASCULAR AND INTERVENTIONAL RADIOLOGY, 2023, 46 (12) : 1715 - 1725
  • [35] Application of machine learning in predicting the adsorption capacity of organic compounds onto biochar and resin
    Zhao, Ying
    Fan, Da
    Li, Yuelei
    Yang, Fan
    ENVIRONMENTAL RESEARCH, 2022, 208
  • [36] Study on adsorption characteristics of biochar on heavy metals in soil
    Hong Wang
    Wen Xia
    Ping Lu
    Korean Journal of Chemical Engineering, 2017, 34 : 1867 - 1873
  • [37] Study on adsorption characteristics of biochar on heavy metals in soil
    Wang, Hong
    Xia, Wen
    Lu, Ping
    KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2017, 34 (06) : 1867 - 1873
  • [38] Evaluating biochar in sustainable stormwater treatment of heavy metals
    Burch, Sarah
    Nason, Jeffrey
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2018, 255
  • [39] Simulation, prediction and optimization for synthesis and heavy metals adsorption of schwertmannite by machine learning
    Liang, Chouyuan
    Zhang, Zhuo
    Li, Yuanyuan
    Wang, Yakun
    He, Mengsi
    Xia, Fang
    Wu, He
    ENVIRONMENTAL RESEARCH, 2025, 265
  • [40] Simulating wastewater treatment plants for heavy metals using machine learning models
    Marwan Kheimi
    Mohammad A. Almadani
    Mohammad Zounemat-Kermani
    Arabian Journal of Geosciences, 2022, 15 (17)
12345