Building artificial neural networks to predict direction and magnitude of wind, current and wave for sailing vessels
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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, optimisation of the route according to these
conditions will improve the factors such as labour, 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—a part of the POSEIDON system. With this information being used, artificial neural networks were trained and three separate artificial neural networks were created, which can predict wind direction and speed, direction and speed of sea current, wave direction and height. For different regions, it is necessary to use artificial neural networks trained using the historical information of those regions. This study is an example of prospective studies.
Keywords: Current, neural network, prediction, sailing vessels, sea, wave, wind
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