About this document
Machine Learning for Chloride Diffusion in Concrete by flahmajdi is a document available to read on EtoBox.
This study investigates the use of machine learning algorithms to predict the chloride diffusion coefficient in concrete, highlighting the inefficiencies of traditional evaluation methods. Various models, including XGBoost, were optimized using particle swarm optimization, with XGBoost showing the best performance (R2 = 0.9382). A comprehensive database was created to analyze the impact of material composition, curing, and exposure conditions on chloride diffusion, ultimately demonstrating the efficacy of m
- Author
- flahmajdi
- Language
- EN