The prediction of deep-sea mining sediment plumes is essential for assessing and mitigating the environmental impacts on vulnerable deep-sea ecosystems. In this paper, the numerical simulation method is adopted to predict the sediment plume transportation. Fluid dynamics are governed by the incompressible Navier–Stokes equations, coupled with the Standard k–ε turbulence model to capture turbulent diffusion. The air–water free...

Accurate forecasting of aquatic production is critical for sustainable fisheries management. In this study, four neural network models, namely Back Propagation (BP) neural network, BP neural networks optimized by Genetic Algorithms (GA-BP), Long Short-Term Memory neural networks (LSTM), and Radial Basis Function neural networks (RBF), are developed and compared to predict aquatic production in Zhanjiang City, China. First, key...