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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Application of Artificial Neural Network into the Water Level Modeling and Forecast
1 Institute of Meteorology and Water Management – National Research Institute, Gdynia, Poland
ABSTRACT: The dangerous sea and river water level increase does not only destroy the human lives, but also generate the severe flooding in coastal areas. The rapidly changes in the direction and velocity of wind and associated with them sea level changes could be the severe threat for navigation, especially on the fairways of small fishery harbors located in the river mouth. There is the area of activity of two external forcing: storm surges and flood wave. The aim of the work was the description of an application of Artificial Neural Network (ANN) methodology into the water level forecast in the case study field in Swibno harbor located is located at 938.7 km of the Wisla River and at a distance of about 3 km up the mouth (Gulf of Gdansk - Baltic Sea).
KEYWORDS: Gulf of Gdansk, Flooding, Coastal Area, Artificial Neural Network (ANN), Hydrography, Wisla River, Water Level Modeling, Multilayer Preceptron
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Citation note:
Sztobryn M.: Application of Artificial Neural Network into the Water Level Modeling and Forecast. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 7, No. 2, doi:10.12716/1001.07.02.09, pp. 219-223, 2013
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