Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure

ISBN-13: 9780128240731 / Miękka / 2023 / 340 str.

Spis treści

1. Integrated schematic design method for shear wall structures: A practical application of generative adversarial networks 2. Leveraging machine learning techniques to support a holistic performance-based seismic design of civil structures 3. Deep learning-based damage inspection for concrete structures 4. Explainable computational intelligence method to evaluate the damage on concrete surfaces compared to traditional visual inspection techniques 5. Smart building fire safety design driven by artificial intelligence 6. The potential of deep learning in dynamic maintenance scheduling for thermal energy storage chiller plants 7. The use of IDA on GPR data to monitor road transport infrastructures 8. Ai for large-scale evacuation modelling: promises and challenges 9. On the application of machine learning classifiers in evaluating liquefaction potential of civil infrastructure 10. Explainable machine learning model for prediction of axial capacity of strengthened CFST columns 11. Harnessing data from benchmark testing for the development of spalling detection techniques using deep learning