Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm-Reference-Cited by-同舟云学术

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Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Published:2023-07 Issue: Volume:385 Page:131519
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Sun Yubo,Cheng Hao,Zhang Shizhe,Mohan Manu K.,Ye Guang,De Schutter Geert

Funder

Horizon 2020

Horizon 2020 Framework Programme

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference95 articles.

1. Cements of yesterday and today: concrete of tomorrow;Aı̈tcin;Cem. Concr. Res.,2000

2. Options for the future of cement;Scrivener;Indian Concr. J.,2014

3. Structural concrete based on alkali-activated binders: Terminology, reaction mechanisms, mix designs and performance;Herrmann;Struct. Concr.,2018

4. Designing precursors for geopolymer cements;Duxson;J. Am. Ceram. Soc.,2008

5. Mechanism, rates, and consequences of basaltic glass dissolution: II. An experimental study of the dissolution rates of basaltic glass as a function of pH and temperature;Gislason;Geochim. Cosmochim. Acta,2003

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