Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation
A Marrel, B Iooss - Reliability Engineering & System Safety, 2024 - Elsevier
In the framework of risk assessment, computer codes are increasingly used to understand,
model and predict physical phenomena. As these codes can be very time-consuming to run …
model and predict physical phenomena. As these codes can be very time-consuming to run …
SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes
Abstract The Surrogate Modeling Toolbox (SMT) is an open-source Python package that
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …
A mixed-categorical correlation kernel for Gaussian process
Recently, there has been a growing interest for mixed-categorical meta-models based on
Gaussian process (GP) surrogates. In this setting, several existing approaches use different …
Gaussian process (GP) surrogates. In this setting, several existing approaches use different …
Outage duration prediction under typhoon disaster with stacking ensemble learning
H Hou, C Liu, R Wei, H He, L Wang, W Li - Reliability Engineering & System …, 2023 - Elsevier
We propose a novel stacking ensemble learning model to predict the outage duration during
typhoon disaster to help users prevent disasters. The model integrates extra tree (ET) …
typhoon disaster to help users prevent disasters. The model integrates extra tree (ET) …
A multi-output multi-fidelity Gaussian process model for non-hierarchical low-fidelity data fusion
Multi-fidelity (MF) surrogate model has been widely used in dealing with computationally
expensive problems as it can make a trade-off between computational cost and modeling …
expensive problems as it can make a trade-off between computational cost and modeling …
Adaptive multi-fidelity Monte Carlo for real-time probabilistic storm surge predictions
Real-time, probabilistic predictions of the expected storm surge represent an important
information source for guiding emergency response decisions during landfalling tropical …
information source for guiding emergency response decisions during landfalling tropical …
Coastal Flood at Gâvres (Brittany, France): A Simulated Dataset to Support Risk Management and Metamodels Development
Given recent scientific advances, coastal flooding events can be modelled even in complex
environments. However, such models are computationally expensive, preventing their use …
environments. However, such models are computationally expensive, preventing their use …
Forecasting of compound ocean-fluvial floods using machine learning
Flood modelling and forecasting can enhance our understanding of flood mechanisms and
facilitate effective management of flood risk. Conventional flood hazard and risk …
facilitate effective management of flood risk. Conventional flood hazard and risk …
A user-oriented local coastal flooding early warning system using metamodelling techniques
Given recent scientific advances, coastal flooding events can be properly modelled.
Nevertheless, such models are computationally expensive (requiring many hours), which …
Nevertheless, such models are computationally expensive (requiring many hours), which …
[HTML][HTML] Integrating physics-based simulations with gaussian processes for enhanced safety assessment of offshore installations
Installing large floating objects during offshore operations is a challenging and failure-prone
task, especially when passing through the splash zone due to extreme lifting loads on the …
task, especially when passing through the splash zone due to extreme lifting loads on the …