Ship Resistance Prediction with Artificial Neural Networks

Kamila Grabowska; Piotr Szczuko

doi:10.1109/spa.2015.7365154

Ship Resistance Prediction with Artificial Neural Networks

Abstract

The paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes parameters of 7 already built off-shore vessels, with model parameters available as a result of tests conducted on European towing tanks. Thus, the reference is used to assess ship resistance prediction with the artificial neural network approach.

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Authors (2)

Kamila Grabowska
Piotr Szczuko dr hab. inż.

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Publication version: Accepted or Published Version
License: Copyright (2015 IEEE)

Keywords

NEURAL NETWORKS

Details

Category:: Conference activity
Type:: materiały konferencyjne indeksowane w Web of Science
Title of issue:: SPA 2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications strony 168 - 173
Language:: English
Publication year:: 2015
Bibliographic description:: Grabowska K., Szczuko P..: Ship Resistance Prediction with Artificial Neural Networks, W: SPA 2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications, 2015, Institute of Electrical and Electronics Engineers (IEEE),.
DOI:: Digital Object Identifier (open in new tab) 10.1109/spa.2015.7365154
Verified by:: Gdańsk University of Technology