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Tytuł artykułu

Application of artificial neural networks to approximation and identification of sea-keeping performance of a bulk carrier in ballast loading condition

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents an application of artificial neural networks to approximation and identification of additional wave-generated resistance, slamming and internal forces depending on ship motion and wave parameters. The analysis was performed for a typical bulk carrier in ballast loading conditions. The investigations were carried out on the basis of ship response data calculated by means of exact numerical methods. Analytical functions presented in the form of artificial neural networks were analyzed with a view of their accuracy against standard values. Possible ways of application of the artificial neural networks were examined from the point of view of accuracy of approximation and identification of the assumed ship response parameters.
Rocznik
Tom
Strony
31--39
Opis fizyczny
Bibliogr. 4 poz., rys., tab.
Twórcy
autor
  • Institute of Marine Navigation, Maritime University of Szczecin Wały Chrobrego 1/2 70-500 Szczecin, POLAND, cepowski@am.szczecin.pl
Bibliografia
  • 1. Karppinen T.: Criteria for Seakeeping Performance Predictions, ESPOO 1987
  • 2. Journée J.M.J.: Verification and Validation of Ship Motions. Program SEAWAY, Report1213a, Delft University of Technology, The Netherlands, 2001
  • 3. Journée J.M.J.: Theoretical Manual of SEAWAY, Report1216a, Delft University of Technology, The Netherlands, 2001
  • 4. Szelangiewicz T.: Ship’s Operational Effectiveness Factor as Criterion for Cargo Ship Design Estimation, Marine Technology Transaction, Polish Academy of Sciences, Branch in Gdańsk, Vol. 11, 2000.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWM3-0017-0009
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