Development of machine learning models for the prediction of the compressive strength of calcium-based geopolymers-Reference-Cited by-同舟云学术

Development of machine learning models for the prediction of the compressive strength of calcium-based geopolymers

Published:2022-12 Issue: Volume:380 Page:135159
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Huo Wangwen,Zhu Zhiduo,Sun He,Ma Borui,Yang Liu

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment,Building and Construction

Reference74 articles.

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2. Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques;Ahmad;Case Stud. Constr. Mat.,2022

3. Geopolymer concrete as a cleaner construction material: an overview on materials and structural performances;Ahmed;Clean. Mater.,2022

4. Systematic multiscale models to predict the compressive strength of fly ash-based geopolymer concrete at various mixture proportions and curing regimes;Ahmed;PLoS One,2021

5. Compressive strength of geopolymer concrete composites: a systematic comprehensive review, analysis and modeling;Ahmed;Eur. J. Environ. Civ. En.,2022

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