极端海况是多种外界因素共同作用的结果,传统单变量波浪预报模型无法考虑多变量的影响,因此构建EMD-LSTM多变量输入模型来预报极端海况。以浮标数据作为分析数据集,利用改进的EMD算法消除变量端点效应和时序非平稳性的影响,运用多变量输入模型对其进行预测分析。结果表明：多变量复合模型可对极端海况实现有效提前预警,输入层引入波高、风速和阵风3个关键因子后模型预报性能最佳,比对均方根误差和纳什效率系数可知多变量输入的预报性能较单变量有显著提升。
Abstract
The extreme sea state is generated by the combined action of various external factors. The traditional univariable wave prediction model cannot consider the influence of multiple variables. Therefore, the EMD-LSTM multivariable input model is constructed to predict the extreme sea state. By using the improved EMD algorithm to process the data set measured by wave buoy, the influence of variable end effect and non-stationarity can be eliminated and thus the prediction accuracy of the multivariable input model can be improved. The results show that the multivariable composite model can make an effective early warning on extreme sea conditions, and the model has the best prediction performance after introducing three key factors such as wave height, wind speed and gust speed into the input layer. Indicated by the root mean square error and Nash-Sutcliffe efficiency, the prediction performance of multivariable input model is significantly improved in comparison with the univariable input model.
关键词
波浪传播 /
预测 /
LSTM /
多变量复合模型 /
端点效应 /
非平稳性
Key words
wave propagation /
prediction /
LSTM /
multivariable composite model /
end effect /
nonstationarity
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基金
国家自然基金（52271337; 52071303）; 山东省自然科学基金（ZR2019BEE042）
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