Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms

Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms

This study presents a methodology to optimize concrete mixtures by integrating machine learning (ML) and genetic algorithms. ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. Using a dataset of over 19,000 samples from a...

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Bibliographic Details
Main Authors: Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez
Format: Article
Language:English
Published: MDPI AG 2024-06-01
Series:Modelling
Subjects:
concrete mixture optimization
genetic algorithm
machine learning estimators
compressive strength prediction
Online Access:https://www.mdpi.com/2673-3951/5/3/34
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