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Machine Learning for Steel Corrosion Assessment by Abinayaa Anbazhakan is a document available to read on EtoBox.

This study presents a hybrid data-driven machine learning approach to evaluate steel corrosion in reinforced concrete by integrating electrical resistivity with concrete performance indicators. Six machine learning algorithms were tested, with results showing that models combining these indicators significantly outperform those using electrical resistivity alone, particularly with Gaussian Process Regression achieving the highest accuracy. The findings highlight the importance of integrating documented conc

Author

Abinayaa Anbazhakan

Language

EN