Machine learning approaches to predict compressive strength of fly ash-based geopolymer concrete: A comprehensive review
Author:
Funder
RMIT University
Australian Research Council
Publisher
Elsevier BV
Reference75 articles.
1. New cements for the 21st century: the pursuit of an alternative to Portland cement;Shi;Cem. Concr. Res.,2011
2. A review of recent developments and advances in eco-friendly geopolymer concrete;Imtiaz;Appl. Sci.,2020
3. Properties of NaOH activated geopolymer with marble, travertine and volcanic tuff wastes;Tekin;Constr. Build. Mater.,2016
4. A machine learning-assisted numerical predictor for compressive strength of geopolymer concrete based on experimental data and sensitivity analysis;Huynh;Appl. Sci.,2020
5. Analyzing the mechanical performance of fly ash-based geopolymer concrete with different machine learning techniques;Peng;Constr. Build. Mater.,2022
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