3 papers
cs.LG2024
Constrained Recurrent Bayesian Forecasting for Crack Propagation
Sara Yasmine Ouerk, Olivier Vo Van, Mouadh Yagoubi
Predictive maintenance of railway infrastructure, especially railroads, is essential to ensure safety. However, accurate prediction of crack evolution represents a major challenge…
cs.LG2023
Hybrid data driven/thermal simulation model for comfort assessment
Romain Barbedienne, Sara Yasmine Ouerk, Mouadh Yagoubi +3
Machine learning models improve the speed and quality of physical models. However, they require a large amount of data, which is often difficult and costly to acquire. Predicting t…
cs.LG2023
Rail Crack Propagation Forecasting Using Multi-horizons RNNs
Sara Yasmine Ouerk, Olivier Vo Van, Mouadh Yagoubi
The prediction of rail crack length propagation plays a crucial role in the maintenance and safety assessment of materials and structures. Traditional methods rely on physical mode…