Method for predicting ship navigation meteorological factors according to marine meteorological information

Abstract

The invention discloses a method of predicting ship navigation meteorological factors according to marine meteorological information. A sample data set is firstly obtained through ship navigation database screening query and data normalization; then, an alternating sparse auto-encoders (ASAE) deep learning regression prediction model is built, based on a large amount of historical ship navigation sample data sets, a least square method, an L2 weight decay constraint and a KL contrast sparsity constraint are adopted to define a cost function, and alternating unsupervised learning and supervised learning are combined for parameter tuning; and finally, to-be-predicted ship navigation data are substituted to the ASAE prediction model with the solved optimize4d parameters for meteorological factor prediction. The method of the invention can build a function relationship between the ship speed and diversified marine meteorological conditions in the ship navigation, the complicated nonlinear problem in meteorological factor calculation can be solved, the meteorological factor prediction precision is improved, and an important role is played in energy-saving emission-reduction navigation optimization.

Description

technical field [0001] The invention belongs to the field of ship shipping, and in particular relates to a method for predicting weather factors of ship navigation according to marine meteorological information. Background technique [0002] The substantial increase in energy consumption and cargo movement in the shipping industry, as well as the increase in the size of ships has led to an increase in shipping carbon emissions. Developed countries are paying more and more attention to the issue of low-carbon emission reduction in the shipping industry. The trend of international shipping carbon emission restrictions has become irreversible. On January 1, 2013, the International Maritime Organization (IMO) enforced the "Ship Energy Efficiency Design Index (EEDI)", "Energy Efficiency Operation Index (EEOI)" and "Ship Energy Efficiency Management Plan (SEEMP)". The development of the work has a strong impetus. "Navigation optimization" is one of the means for ships to save ene...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the above shortcomings, the present invention provides a method for predicting meteorological factors of ship navigation based on marine meteorological information, which can solve the problem of forecasting meteorological factors in the influence of marine meteorology on ship navigation, and comprehensively consider the performance of the ship itself, ship navigation data and marine meteorological factors. Changes and other factors, from the perspective of machine learning, big data technology and statistics, by constructing an alternating sparse autoencoder (ASAE) deep learning regression prediction model for model training and parameter optimization, and finally a meteorological factor prediction model for solving Accurate Prediction of Influence of Marine Meteorological Factors on Vessel Velocity

Images