期刊论文

Yang, Zequn;Li, HL

英文

PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-ENERGY

1751-4223

2024

288

129854

10.1016/j.energy.2023.129854

CRediT authorship contribution statement Lijian Leng: Conceptualization, Supervision, Writing – original draft, Writing – review & editing, Project administration, acquisition. Junhui Zhou: Data collection, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. Weijin Zhang: Methodology, Writing – review & editing. Jiefeng Chen: Writing – review & editing. Zhibin Wu: Resources. Donghai Xu: Resources. Hao Zhan: Resources. Xingzhong Yuan: Writing – review & editing. Zhengyong Xu: Resources.

本校为其他机构

Hydrochar serves not only as a fuel source but also as a versatile carbon material that has found extensive application across various domains. The application performance of hydrochar, e.g., energy recovery and carbon stability, is substantially influenced by its mass yield, higher heating value (HHV), and compositions (C, H, O, N, S, and ash), so the prediction and engineering of these properties is promising. In this study, two machine learning algorithms, namely gradient boosting regression (GBR) and random forest (RF), were used to predict the hydrochar properties mentioned above. The GBR...