Comparative analysis of machine learning techniques for predicting flexural behavior in RC beams

Key Points

• Flexural behavior predictions outperform traditional methods, significantly enhancing structural analysis accuracy.
• Machine learning techniques, notably random forest and neural networks, showed the best predictive performance in testing.
• Analysis utilizes historical data from reinforced concrete beam tests and various machine learning algorithms for comparison.
• These findings indicate the potential for machine learning to transform engineering practices in structural assessments.