A Markov Prediction Model for Sea-Level Fluctuations Based on Wave Spectrum

As global attention to ocean resources intensifies and the activities of ocean resource development deepen, accurately predicting sea-level fluctuations becomes crucial for ensuring the safety and efficiency of ocean exploration. This study aims to enhance the safety and efficiency of maritime operations through an in-depth analysis of sea-level fluctuations. The study employs wave spectrum for numerical simulation to analyze the energy distribution of waves at different frequencies and uses linear superposition of cosine waves to simulate changes in sea-level fluctuations. Subsequently, based on the simulation results, a Markov model’s state transition probability matrix is constructed to predict changes in sea-level fluctuations. This research achieves short-term predictions of sea-level fluctuations. In the final part of the article, measures that should be taken to improve prediction accuracy are discussed, such as s applying deep learning techniques and considering the coupling effects among wind, waves, and currents.