The invention discloses a ship body local vibration prediction method based on an SA-XGBOOST algorithm. The ship body local vibration prediction method comprises the following steps of obtaining a plurality of groups of historical vibration data of local vibration measurement points when a ship sails; performing dimension reduction processing on the historical vibration data to obtain dimension-reduced vibration data; the method comprises the following steps of: training and testing a ship body local vibration prediction model by utilizing dimension reduction vibration data based on an XGBOOST algorithm, optimizing XGBOOST parameters by utilizing a simulated annealing algorithm in an iterative calculation process of training and testing to obtain an optimal XGBOOST parameter combination, and substituting the optimal XGBOOST parameter combination into the model to carry out a next round of iterative calculation, so that a ship body local vibration prediction model is obtained. The accuracy of the ship body local vibration prediction model meets the requirement. And predicting local vibration data of the to-be-measured position by using the ship body local vibration prediction model. According to the method, the precision of the ship body local vibration prediction model is improved, the model is prevented from falling into local optimum, and the robustness of the algorithm is improved.
本发明公开了一种基于SA‑XGBOOST算法的船体局部振动预测方法,包括以下步骤:获取船舶航行时局部振动测量点的若干组历史振动数据;对历史振动数据进行降维处理,获得降维振动数据;基于XGBOOST算法,利用降维振动数据对船体局部振动预测模型进行训练和测试,在进行训练和测试的迭代计算过程中,利用模拟退火算法对XGBOOST参数进行优化,得到最优的XGBOOST参数组合,并将最优的XGBOOST参数组合代入模型以进行下一轮的迭代计算,直至得到准确率满足要求的船体局部振动预测模型;利用船体局部振动预测模型预测待测量位置的局部振动数据。本发明在提高了船体局部振动预测模型精度的同时,防止模型陷入局部最优,提高了算法的鲁棒性。
Ship body local vibration prediction method based on SA-XGBOOST algorithm
一种基于SA-XGBOOST算法的船体局部振动预测方法
10.01.2025
Patent
Elektronische Ressource
Chinesisch
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