Comparative Analysis of Machine Learning Techniques for Concrete Compressive Strength Prediction
Author:
Affiliation:
1. University of Bahrain,Civil Engineering Department,Isa Town,Kingdom of Bahrain
2. Al Iman School,Computer Department,Isa Town,Kingdom of Bahrain
3. University of Bahrain,Electrical Engineering Department,Isa Town,Kingdom of Bahrain
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10629220/10629232/10629479.pdf?arnumber=10629479
Reference15 articles.
1. Toward improved prediction of recycled brick aggregate concrete compressive strength by designing ensemble machine learning models
2. Machine Learning-Based Method for Predicting Compressive Strength of Concrete
3. Compressive strength prediction of high-strength concrete using machine learning
4. Study on predicting compressive strength of concrete using supervised machine learning techniques
5. Concrete compressive strength prediction using an explainable boosting machine model
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