中文摘要：

独居的波浪助跑的预言有重要实际意义在沿海并且海洋工程，而是计算精确在存在模型被限制。为改进计算精确，一个独居的波浪助跑计算模型在这研究基于人工的神经网络被建立。有一隐藏的层的一个背繁殖(BP ) 网络与另外的动量方法和调整汽车的学习因素被采用并且修改。模型被用于独居的波浪助跑的计算。在神经网络之间的关联系数为结果和试验性的价值建模是 0.996 5。由有关联系数的比较 0.963 5 神经网络模型是为独居的波浪助跑的计算和分析的一个有效方法，这在 Synolakis 公式计算结果和试验性的值之间，被结束。

英文摘要：

The prediction of solitary wave run-up has important practical significance in coastal and ocean engineering, but the calculation precision is limited in the existing models. For improving the calculation precision, a solitary wave run-up calculation model was established based on artificial neural networks in this study. A back-propagation （BP） network with one hidden layer was adopted and modified with the additional momentum method and the auto-adjusting learning factor. The model was applied to calculation of solitary wave run-up. The correlation coefficients between the neural network model results and the experimental values was 0.996 5. By comparison with the correlation coefficient of 0.963 5, between the Synolakis formula calculation results and the experimental values, it is concluded that the neural network model is an effective method for calculation and analysis of solitary wave ran-up.