structural reliability analysis

TL-GPRSM: A python software for constructing transfer learning Gaussian process regression surrogate model with explainability

Software Impacts (**Impact Factor: 2.1** in 2022)

Transfer learning Gaussian process regression surrogate model with explainability for structural reliability analysis under variation in uncertainties

Computers & Structures (**Impact Factor: 5.372** in 2021; [Structural Engineering at Google Scholar Metrics](https://scholar.google.com/citations?view_op=top_venues&hl=en&vq=eng_structuralengineering))

Gaussian process regression surrogate model for dynamic analysis to account for uncertainties in seismic loading

Reliability assessment of civil structures under seismic loads requires probabilistic evaluation considering the uncertainty of input ground motion and material properties due to deterioration. However, Monte Carlo calculation for the structural …

Gaussian Process Regression Surrogate Model for Seismic Vulnerability Assessment of Highway Bridge Structure System

System fragility is required especially for the vulnerability assessment of existing bridges that configure transportation network as a structural system. Here, it is essential to consider not only variation of input ground motions but also the …