Tidal-level prediction is crucial for ensuring the safety and efficiency of offshore marine activities, port and channel management, water transportation resource development, and life-saving operations. Although tidal harmonic analysis is among the most prevalent methods for predicting tidal water level fluctuations, it relies on extensive data, and its long-term prediction accuracy can be limited. To enhance prediction performance, this paper proposes a model that combines the variational mode decomposition (VMD) algorithm with the long short-term memory (LSTM) neural network. The initial step involves decomposing the original data using the VMD algorithm, followed by applying the LSTM to each decomposition component. Finally, all prediction results are superimposed and summed. The model is tested using the 2018 tidal time series data from the Lvsi station in Zhoushan City and the 2020 tidal time series data from the Ganpu station. The results are compared with those from the classical harmonic analysis model, the traditional machine learning model, and the decomposition-based machine learning method. The experimental outcomes demonstrate the superior predictive capabilities of the proposed model.

The wave resistance of a buoy is affected by the mode of anchorage and the buoy structure. Combining the structures and the mode of anchorage of the existing buoys, designing a buoy with significantly improved wave resistance is a major challenge for marine environment monitoring. This work carried out experimental and numerical simulation studies on the hydrodynamic properties of a self-designed symmetrical three-cylinder buoy. The wave resistance of the buoy was analyzed using different wave conditions, and a full-scale simulation of the buoy was performed using the finite element method and lumped mass method. Experimentally, it was found that the symmetrical three-cylinder buoy stability was less affected by the wave height, but mainly by the wave period. Additionally, the effects of wave height and wave period on mooring tension were also studied, and the results showed that mooring tension was mainly affected by wave period, which was explained by the rate of change of the buoy momentum. Finally, a numerical model was proposed for the interpretation of these experiments. Results from numerical simulations for the trajectory of the buoy and the tension of the mooring cable correlated well with the experimental data.