基于机器学习代理的深度集成模型的频散

Maile McCann, Patrick Lynett, Behzad Ebrahimi
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引用次数: 0

摘要

Boussinesq型波浪模型具有解析沿海地区波浪传播的准确性,能够捕捉近岸动力学,包括相对短波的非线性和色散效应。与利用非线性浅水(NLSW)方程的对应模型相比,Boussinesq型模型的精度为研究近岸过程提供了明显的优势。然而,在NLSW解决方案上寻找Boussinesq解决方案的计算费用阻碍了使用Boussinesq类型模型的快速和/或实时仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FREQUENCY DISPERSION IN DEPTH-INTEGRATED MODELS THROUGH MACHINE LEARNING SURROGATES
Boussinesq- type wave models have the accuracy to resolve wave propagation in coastal zones, having the ability to capture nearshore dynamics that include both nonlinear and dispersive effects for relatively short waves. The accuracy of Boussinesq type models over their counterparts which utilize the non- linear shallow water (NLSW) equations provides a clear advantage in studying nearshore processes. However, the computational expense of finding the Boussinesq solution over the NLSW solution hinders fast and/ or real time simulation using Boussinesq type models.
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