Deep learning-based sea wave height prediction method and application thereof

Abstract

The invention discloses a deep learning-based sea wave height prediction method and application thereof, and the method comprises the steps: respectively inputting sea wave data information into an AM-LSTM model and a CatBoost model, obtaining and outputting P1 and P2, and reconstructing P1 and P2 according to the following formula to obtain a prediction sequence P; p = q2 * P1 + q1 * P2, w1 is the mean value of the MAE, the RMSE and the MAPE output by the AM-LSTM model, and w2 is the mean value of the MAE, the RMSE and the MAPE output by the CatBoost model. According to the sea wave height prediction method, the advantages of the LSTM in deep learning in the aspect of processing long-term data prediction, the characteristics of the attention mechanism and the characteristics of few parameters, fast training and difficult overfitting of the CatBoost are considered, the predicted data are reconstructed, the prediction precision is high, the generalization performance is high, the method is especially suitable for sea wave height prediction, and the application prospect is promising.

Description

technical field [0001] The invention belongs to the technical field of time series prediction, and relates to a deep learning-based sea wave height prediction method and its application, in particular to a deep learning and CatBoost-based multivariable sea wave height prediction method and its application. Background technique [0002] In recent years, the focus of human exploration has gradually shifted from land to sea. The development and utilization of marine resources such as mariculture, marine transportation, and coastal tourism have greatly promoted economic output. All countries and major coastal countries in the world have fully realized the strategic significance of developing marine economy. Wave height is one of the important parameters in oceanographic research, and its changes will have a great impact on offshore operations, port construction, and coastal residents' lives, and even lead to extreme situations such as the suspension of coastal activities and the...

AI Technical Summary

Problems solved by technology

[0010] The purpose of the present invention is to overcome the defects of the existing wave height prediction method that the data requirements and processing capacity are large, the adaptability is poor, and the relationship between the wave height data cannot be fully excavated, and a method with small data requirements and processing capacity, good adaptability and high adaptability is provided. A wave height prediction method that can fully mine the relationship between wave height data

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