The increased trends of extreme precipitation events over China have been partially attributed to global warming, while it is unclear how the natural climate iability affect these …
We develop a memory graph convolutional network (MGCN) framework for sea surface temperature (SST) prediction. The MGCN consists of two memory layers: one graph layer and one …
This paper proposes a nonlocal fractional peridynamic (FPD) model to characterize the nonlocality of physical processes or systems, based on analysis with the fractional derivative …
We investigate the problem of training an oil spill detection model with small data. Most existing machine-learning-based oil spill detection models rely heavily on big training …
Autumn Arctic sea ice has been declining since the beginning of the era of satellite sea ice observations. In this study, we examined the factors contributing to the decline of …
Autumn Arctic sea ice has been declining since the beginning of the era of satellite sea ice observations. In this study, we examined the factors contributing to the decline of …
Numerical models and correct predictions are important for marine forecasting, but the forecasting results are often unable to satisfy the requirements of operational wave …
Textures contain a wealth of image information and are widely used in various fields such as computer graphics and computer vision. With the development of machine learning, the …
Accurately predicting wave height has a significant impact on offshore production and marine transportation. Numerical model predictions are the most commonly used wave height …
