Over a decade ago, an analogy was drawn between the generation of large ocean waves
and the propagation of light fields in optical fibres. This analogy drove numerous …

Coastal bridges are vulnerable to complicated hydrodynamics induced by hostile natural
hazards, relevant research is thus required to ensure the safe operation of these critical …

A machine learning framework is developed to estimate ocean-wave conditions. By
supervised training of machine learning models on many thousands of iterations of a …

Promising new opportunities to apply artificial intelligence (AI) to the Earth and
environmental sciences are identified, informed by an overview of current efforts in the …

We present a new deep learning training framework for forecasting significant wave height
on the Southwestern Atlantic Ocean. We use the long short-term memory algorithm (LSTM) …

A machine learning framework based on a multi-layer perceptron (MLP) algorithm was
established and applied to wave forecasting in Lake Michigan. The MLP model showed …

With climate change impacts like sea level rise and changing storms, proper prediction of
significant wave height (SWH) becomes increasingly important for coastal protection and …

In situ and remotely sensed observations have potential to facilitate data-driven predictive
models for oceanography. A suite of machine learning models, including regression …

Accurate prediction of wave characteristics of large-scale waves is of great significance for
ocean disaster prevention and shipping safety. The traditional method is mainly based on …

Ocean waves are widely estimated using physics-based computational models, which
predict how energy is transferred from the wind, dissipated, and transferred spatially across …