Machine learning to predict properties of fresh and hardened alkali-activated concrete

被引：1
|
作者：
Gomaa, Eslam [1 ]
Han, Taihao [2 ]
ElGawady, Mohamed [1 ]
Huang, Jie [3 ]
Kumar, Aditya [2 ]
机构：
[1] Department of Civil, Architectural, and Environmental Engineering, Missouri University of Science and Technology, Rolla,MO,65409, United States
[2] Department of Materials Science and Engineering, Missouri University of Science and Technology, Rolla,MO,65409, United States
[3] Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla,MO,65409, United States
来源：
Cement and Concrete Composites | 2021年 / 115卷
基金：
美国国家科学基金会;
关键词：
Forecasting - Random forests - Decision trees - Fly ash - Portland cement - Machine learning - Concretes;
D O I：
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中图分类号：
学科分类号：
摘要：
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