Based on the FOA algorithm research of ocean-going vessels economy speed

In this paper, aiming at the non-linear characteristics of ocean-going sailing vessel model and the deficiencies of either the traditional mathematical methods or the neural networking modeling, an improved support vector regression (SVR) economical sailing predictive modeling method based on the fly fruit optimization algorithm (FOA) is proposed. First, using data mining techniques on the ship sailed data mining, screening, then use the processed data to establish economic sailing forecast model of the ocean-going vessels. The model synthetically considers the external natural variables which influence on the ocean-going sailing vessel and provides the economical way of sailing under the multi-variable natural weather conditions. The simulation results show that this model is able to accurately predict the pitch for the economical sailing control according to the external multivariable. It has been certificated that this method is an effective novel means to study the economical sailing control of the ocean-going vessel.