基于注意机制的序列对序列波谱预测模型

Xiao Zeng, Lin Qi, Tong Yi, Tong Liu
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引用次数: 0

摘要

海浪谱的估计主要来自于波面记录,传统的方法包括基于物理的波浪动力学建模和频率分析。在本文中,我们采用机器学习策略并提出了一个Seq2Seq (sequence to sequence)模型,该模型通过注意机制将编码器和解码器连接起来。该模型既能有效地预测波浪谱,又易于实现。数值模拟实验证明了该模型在波浪谱估计方面的可行性和与传统方法相比的准确性。
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A Sequence-to-Sequence Model Based on Attention Mechanism for Wave Spectrum Prediction
Ocean wave spectrum are mainly estimated from wave surface records, and traditional methods involve physically-based modeling of wave dynamics and frequency analysis. In this paper, we employ machine learning strategy and propose a Seq2Seq (sequence to sequence) model which connects the encoder and decoder with an attention mechanism. This model can both effectively predict wave spectrum and be easily implemented. Experiments on numerical simulations show the feasibility of the proposed model in wave spectrum estimation and the accuracy comparing with traditional methods.
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