The invention discloses a ship initial stability height prediction method, device and system, and a storage medium. The method comprises the following steps: S1, obtaining historical ship type parameters; s2, selecting key factors related to GM through grey correlation analysis according to historical ship type parameters, and training an RBF neural network; s3, performing hyper-parameter optimization on the trained RBF neural network by using a Bayesian optimization algorithm; and S4, inputting the ship type parameters to be processed into the optimized and trained RBF neural network to predict the initial stability height of the ship. According to the technical scheme of the invention, the grey correlation analysis and Bayesian optimization algorithms are introduced, so that the prediction precision is effectively improved, the prediction error is reduced, and a more accurate prediction effect is achieved.
本发明公开一种船舶初稳性高度预测方法和装置、系统、存储介质,包括:步骤S1、获取历史船型参数;步骤S2、根据历史船型参数,通过灰色关联分析选取与GM相关的关键因素,训练RBF神经网络;步骤S3、使用贝叶斯优化算法对训练好的RBF神经网络进行超参数优化;步骤S4、将待处理的船型参数输入优化后训练好的RBF神经网络中进行船舶初稳性高度预测。采用本发明的技术方案,通过引入灰色关联分析和贝叶斯优化算法,有效提高了预测精度,降低了预测误差,达到更加精准的预测效果。
Ship initial stability height prediction method, device and system, and storage medium
船舶初稳性高度预测方法和装置、系统、存储介质
2024-12-13
Patent
Electronic Resource
Chinese
IPC: | B63B Schiffe oder sonstige Wasserfahrzeuge , SHIPS OR OTHER WATERBORNE VESSELS |
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