Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion

文献类型： 外文期刊

第一作者： Zhang, Yi

作者： Zhang, Yi;Feng, Yijing;Ren, Zhonghao;Zuo, Runguo;Zhang, Tianhui;Li, Yeqing;Sun, Ziyan;Liu, Zhiyang;Wang, Yajing;Pan, Junting;Han, Yongming;Feng, Lu;Aghbashlo, Mortaza;Tabatabaei, Meisam;Tabatabaei, Meisam

作者机构：

关键词： Machine learning; Anaerobic digestion; Biochar; Methane production

期刊名称：BIORESOURCE TECHNOLOGY （ 影响因子：11.4； 五年影响因子：10.6 ）

ISSN： 0960-8524

年卷期： 2023 年 374 卷

页码：

收录情况： SCI

摘要： The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3-0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序