著者

松村 竹実 浦 環

出版者

公益社団法人日本船舶海洋工学会

雑誌

日本造船学会論文集 (ISSN:05148499)

巻号頁・発行日

no.183, pp.91-100, 1998-06

被引用文献数

4 1

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This paper proposes an artificial neural network system for regressive estimation of wave making resistance, which is significantly important in preliminary design of high-speed ship. The neural network can explicitly realize nonlinear mapping between hull form and wave making resistance. The system is composed of two kinds of neural networks ; Estimating Net and Descriptive Net. The Estimating Net learns the relation between hull form parameters and wave making resistance coefficients from a number of model-resistance test data. Consequently, when Froude Number, principal particular rations, and area curve parameters of a hull form are given, the Estimating Net of the learned data points in the hull form parameters space. It provides the information about the density of the learned data at the input point in the above parameters' space. In this paper, the test data of 62 models : Series 60, are used for the construction of the system. The leaning is successful and the results of playback calculation show good agreement with the original test data. Some applicable cases for non-learned hull forms are also explained. It is shown that the accuracy of the estimation is in accordance with the output of the Descriptive Net. When other model test data are available, it is easy to modify the constructed system, taking advantage of leaning ability of neural networks.