Prediction of geostrophic currents using big weather data archive and neural networks for the Aegean Sea

Autor: Timur Inan, Ahmet Fevzi Baba
Rok vydání: 2019
Předmět:
Zdroj: Global Journal of Computer Sciences: Theory and Research. 9:10-20
ISSN: 2301-2587
DOI: 10.18844/gjcs.v9i1.4091
Popis: 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.
Databáze: OpenAIRE