Operator learning for predicting bulk wave parameters of spectral wave models
This work explores a proof-of-concept application of Deep Operator Networks (DeepONets) as a surrogate for the Simulating WAves Nearshore (SWAN) numerical wave model, and demonstrates consistently high accuracy in predicting the significant wave height and the x- and y- components of the radiation stress gradient.
Shukai Cai, Sourav Dutta, Mark Loveland et al.
· Ocean Engineering · 0 citations