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Ship Performance Research Based on BP Neural Network

机译:基于BP神经网络的船舶绩效研究

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The problem is solved that it is hard to provide analysis formulas about the maximum equivalent stress, the maximum shear stress and the structural geometric parameters for a ship. The finite element calculation is done with orthogonal experimental design under the most dangerous case. The data obtained are used as the training and test samples to establish BP neural network models of ship's maximum equivalent stress and maximum shear stress. With the aid of Neural network toolbox in MATLAB, the topological structure of BP neural network mapping relationship between the whole ship performance indexes and design variables is established. The training and testing are completed with the data tested by the shipyard and the correctness of this network is verified. The neural network required for further optimization design is obtained. The neural network is helpful in reducing the ship mass without exceeding the allowable stress.
机译:解决问题是,很难提供关于船舶最大等效应力,最大剪切应力和结构几何参数的分析公式。在最危险的情况下用正交的实验设计完成有限元计算。所获得的数据用作培训和测试样本,以建立船舶最大等效应力和最大剪切应力的BP神经网络模型。借助MATLAB的神经网络工具箱,建立了整船性能指标和设计变量之间的BP神经网络映射关系的拓扑结构。训练和测试完成了造船厂测试的数据,并验证了该网络的正确性。获得进一步优化设计所需的神经网络。神经网络有助于减少船舶质量而不超过允许的应力。

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