Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design.

ABSTRACT: The design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering and difficulty predicting concrete properties. Machine learning-based methods offer a solution, as they have proven effective in predicting concrete compressive strength for concrete mix design. This paper scrutinises the association between the computational complexity of machine learning models and their proficiency in predicting the compressive strengt

SUBMITTER: Ziolkowski P 

PROVIDER: S-EPMC10489033 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature