Building artificial neural networks to predict direction and magnitude of wind, current and wave for sailing vessels

Abstract

Current, wind, wave direction and magnitude are important factors affecting the course of ships. These factors may act positively or negatively depending on the course of a vessel. In both cases, optimization of the route according to these conditions, will improve the factors such as labor, fuel and time. In order to estimate the wind, wave, current direction and magnitude for the region to be navigated, it is necessary to develop a system that can make predictions by using historical information. Our study uses historical information from the E1M3A float, which is a part of the POSEIDON system. With this information being used, artificial neural networks were trained and three separate artificial neural networks were created. Artificial neural networks can predict wind direction and speed, direction and speed of sea current, wave direction and heigth. The esmitations made by this system are only valid for the region where the float is located. For different regions, it is necessary to use artificial neural networks trained using the historical information of those regions. This study is an example for prospective studies.