Prediction of time-dependent concrete mechanical properties based on advanced deep learning models considering complex variables

Author:

Jiang Yu,Zhang Jinhao,Zuo Wenqiang,Xu Guodong,Yuan Chi,Wang Longbao,Du Zhirong,Lu Yucan,She Wei

Funder

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference60 articles.

1. Predictive models for concrete properties using machine learning and deep learning approaches: a review;Mohtasham Moein;J. Build. Eng.,2023

2. A comparative study on the mechanical properties, autogenous shrinkage and cracking proneness of alkali-activated concrete and ordinary Portland cement concrete;Li;Constr. Build. Mater.,2021

3. Long-term shrinkage and mechanical properties of fully recycled aggregate concrete: testing and modelling;Zhang;Cem. Concr. Compos.,2022

4. The mechanical property and frost resistance of roller compacted concrete by mixing silica fume and limestone powder: experimental study;Shen;Constr. Build. Mater.,2020

5. Mechanical performance enhancement of recycled aggregate concrete using GGBS and fly ash for sustainable construction;Sarma;Multiscale Multidiscip. Model. Exp. Des.,2023

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