Main Article Content
Prediction of sea and weather environment variables like wind speed, wind direction, wave height, wave direction, sea surface current direction and magnitude has always been an important subject in marine engineering as they effect on ship speed and effect the time of arrival to destination point as well. In this study, we propose a neural network that can predict the latitudinal and longitudinal components of sea surface currents in the Aegean Sea. The system can predict the sea surface currents components using the wind components which are gathered from the INMARSAT weather report system. The neural network is trained using the historical data which is gathered from UCAR historical weather database and historical surface current data which is gathered from IFREMER database.
Keywords: Sea surface current, weather report, prediction, neural network, big data archive.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (SeeThe Effect of Open Access).