[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research

Wave-making Resistance Estimation Through Deep Learning Considering the Distribution of Ship Figure

Bibliographic Information

Other Title
  • 船型データの分布を考慮した深層学習による造波抵抗推定
  • センケイ データ ノ ブンプ オ コウリョ シタ シンソウ ガクシュウ ニ ヨル ゾウハ テイコウ スイテイ

Search this article

Abstract

<p>A method for the estimation of wave-making resistance from the hull form and Froude number through deep learning is proposed. At the same time, this research also gives a solution when the data are skewed, which solves the problem of low generalization performance. The reduction of wave-making resistance is an essential issue in hull form design. However, the estimation of wave-making resistance is a time-consuming task that depends on experimental measurements. To enable direct estimation of the wave resistance from hull form, deep learning, which enables end-to-end learning, is an effective approach. The proposed method has two phases. First, auto-encoders, which reduce the dimension of the offset and the profile data, are generated, while performing to the skewed offset data, use an improved sampling method. Subsequently, after the regularization of these data, a deep neural net for regression estimation of wave-making resistance is generated. The results of evaluation experiments show that the proposed method can estimate wave-making resistance with high precision.</p>

Journal

Citations (0)*help

See more

References(3)*help

See more

Related Articles

See more

Related Data

See more

Related Books

See more

Related Dissertations

See more

Related Projects

See more

Related Products

See more

Details

Report a problem

Back to top