Abstract:Oceanic internal solitary waves are a type of wave motion that occurs within the stable stratified layers of seawater, widely distributed in various oceans worldwide. They play a crucial role in the transfer of material energy and ocean circulation, and have significant impacts on marine engineering construction and the safety of ship navigation. Accurate detection and identification of internal solitary waves in the ocean are of great research value for enhancing our understanding of physical oceanography and maintaining the safety of the marine environment. Traditional methods for detecting and identifying internal solitary waves mainly rely on image processing techniques such as wavelet analysis and edge detection, which require manual intervention and are easily influenced by human judgment. With the development of artificial intelligence, machine learning methods have shown significant superiority in the detection and identification of internal solitary waves, especially in terms of accuracy and automation. In addition, machine learning methods have also made certain progress in research on parameter inversion and propagation prediction of internal solitary waves.