Ship resistance prediction with Artificial Neural Networks

K. Grabowska, P. Szczuko
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引用次数: 13

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.
基于人工神经网络的船舶阻力预测
研究了一种基于人工神经网络(ANN)的船舶阻力预测新方法。在初始阶段,选定的船舶参数准备用作训练集和验证集。下一步是验证几个网络结构,并确定对结果电阻影响最大的参数。最后,提出了影响电阻的其他参数。这项研究利用了7艘已经建造的近海船只的参数,并通过在欧洲拖曳水箱上进行的测试获得了模型参数。从而为利用人工神经网络方法进行船舶阻力预测评估提供了参考。
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