About this document
Machine Learning for Seismic Fragility Assessment by Ahmet is a document available to read on EtoBox.
This paper presents a machine learning-based tool for assessing the seismic fragility and vulnerability of reinforced concrete structures, aimed at improving retrofitting strategies. Utilizing various ML algorithms and hyperparameter optimization techniques, the study significantly reduces computational efforts while achieving high accuracy in predicting seismic fragility curves based on a large dataset derived from Incremental Dynamic Analyses. The proposed methods, including a user-friendly Graphical User
- Author
- Ahmet
- Language
- EN