首页|期刊导航|Artificial Intelligence in Geosciences|Interpretable machine learning models for evaluating strength of ternary geopolymers

Interpretable machine learning models for evaluating strength of ternary geopolymers

Junfei Zhang Huisheng Cheng Ninghui Sun Zehui Huo Junlin Chen

Artificial Intelligence in Geosciences2025，Vol.6Issue(2)：P.40-52,13.

Artificial Intelligence in Geosciences2025，Vol.6Issue(2)：P.40-52,13.DOI:10.1016/j.aiig.2025.100128

Interpretable machine learning models for evaluating strength of ternary geopolymers

Junfei Zhang ¹Huisheng Cheng ¹Ninghui Sun ²Zehui Huo ³Junlin Chen⁴

作者信息

1. School of Civil and Transportation Engineering,Hebei University of Technology,Tianjin,300401,China
2. School of Chemical and Environmental Engineering,China University of Mining and Technology(Beijing),Beijing,100083,China
3. CCCC Tianjin Port Engineering Design&Consulting Co.,Ltd.,Tianjin,300461,China
4. School of Minerals and Energy Resources Engineering,University of New South Wales,Sydney,NSW 2052,Australia
折叠

摘要

关键词

Geopolymer/Solid waste/Mix proportion/Machine learning/Unconfined compressive strength

分类

信息技术与安全科学

引用本文复制引用

Junfei Zhang,Huisheng Cheng,Ninghui Sun,Zehui Huo,Junlin Chen..Interpretable machine learning models for evaluating strength of ternary geopolymers[J].Artificial Intelligence in Geosciences,2025,6(2):P.40-52,13.

基金项目

support provided by the Natural Science Foundation of China(Grant No.52208240) （Grant No.52208240）

S&T Program of Hebei(Grant No.E2022202051,236Z3809G) （Grant No.E2022202051,236Z3809G）

Education Department of Hebei Province(Grant No.:C20220311) （Grant No.:C20220311）

Hebei University of Technology(Grant No.:24/424132021). （Grant No.:24/424132021）

Artificial Intelligence in Geosciences

ISSN：2666-5441

访问量1

下载量0

段落导航