Predicting Ship Responses in Different Seaways using a Generalizable Force Correcting Machine Learning Method

arXiv:2405.08033v1 Announce Type: new
Abstract: A machine learning (ML) method is generalizable if it can make predictions on inputs which differ from the training dataset. For predictions of wave-induced ship responses, generalizability is an important consideration if ML methods are to be useful in design evaluations. Furthermore, the size of the training dataset has a significant impact on the practicality of a method, especially when training data is generated using high-fidelity numerical tools which are expensive. This paper considers a …

abstract arxiv cs.lg dataset design inputs machine machine learning physics.flu-dyn predictions responses ship stat.ml training type