基于BP网络的船舶运动姿态预测

Ge Yang, Qin Ming Jie, Niu Tao
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引用次数: 10

摘要

在对舰船扰动进行补偿时,不能及时得到具体的运动参数。为了解决这一问题,需要对运动姿态进行提前预测,同时也需要为波浪补偿系统提供可靠的数据。介绍了一种基于BP神经网络的运动姿态预测方法。该方法通过选择BP神经网络模型解决了隐层的学习问题,结果表明,该方法可以有效提高运动姿态的预测速度和精度。
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Prediction of ship motion attitude based on BP network
When the disturbance of ship is compensated, it can't get the specific motion parameters in time. In order to solve this problem, the motion attitude needs to be predicted in advance, and the reliable data also needs to be provided for the wave compensation system. This paper introduces a method of motion attitude prediction based on BP neural network. The method solves the learning problem of hidden layer by selecting the BP neural network model, and the results show that using such method can effectively improve the prediction speed and precision of motion attitude.
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