A metaheuristic-guided machine learning approach for concrete strength prediction with high mix design variability using ultrasonic pulse velocity data

Author:

Selcuk S.ORCID,Tang P.ORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Materials Science (miscellaneous),Building and Construction,Civil and Structural Engineering,Architecture

Reference75 articles.

1. Characterization and deterioration detection of Portland cement concrete using ultrasonic waves;Al-Akhras;Virginia Tech,1995

2. Prediction of concrete compressive strength using supervised machine learning models through ultrasonic pulse velocity and mix parameters;Albuthbahak;Romanian Journal of Materials,2019

3. Steam Cured Self-Consolidating Concrete and the Effects of Limestone Filler;Aqel,2016

4. Data on the physical and mechanical properties of soilcrete materials modified with metakaolin;Asteris;Data Brief,2017

5. Feed-forward neural network prediction of the mechanical properties of sandcrete materials;Asteris;Sensors,2017

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