Modular Tide Prediction Model Based on Improved Wavelet Neural Network

In order to make tide prediction more efficient and accurate, this paper proposes a method based on adding momentum term to optimize wavelet neural network for modular tide prediction. In the study, the tides are divided into astronomical tides which are affected by the tidal force of celestial bodies and non astronomical tides which are affected by environmental factors and other factors. The harmonic analysis method and wavelet neural network are used to predict the tides respectively. When using wavelet neural network to predict non astronomical tide, the method of adding momentum term is used to optimize the weight and parameters of wavelet neural network to improve the prediction accuracy. The simulation experiment is carried out by using the data measured at Tampa tide station in western Florida. The results show that the tide prediction model can improve the prediction accuracy and is efficient and feasible.