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首页> 外文期刊>Bulletin of the American Physical Society >APS -70th Annual Meeting of the APS Division of Fluid Dynamics- Event - Application of fuzzy C-means clustering to geophysical transport
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APS -70th Annual Meeting of the APS Division of Fluid Dynamics- Event - Application of fuzzy C-means clustering to geophysical transport

机译：APS-流体动力学APS分部第70届年会-事件-模糊C均值聚类在地球物理运输中的应用

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Lagrangian techniques have been used to identify the underlying structures of time varying flows. The fuzzy C-means trajectory clustering is one such approach, which is based on the partitioning of trajectories into sets that remain close in Euclidean space throughout the interval of study. We apply this method first to an analytic geophysical system to determine a procedure that produces robust clusters and to determine characteristics of systems suitable for fuzzy C-means analysis. One challenge of the method is the initial seeding dependence of clustering results, which requires multiple implementations to confirm robustness. Direct comparison with the spectral clustering method demonstrates the limitations of applying the fuzzy C-means method to systems with a large number of coherent structures. We then apply our procedure to a geophysical fluid dynamics numerical simulation to visualize the dominant mechanism of transport.
机译：拉格朗日技术已被用来识别时变流的潜在结构。模糊C均值轨迹聚类就是这样一种方法，它是基于将轨迹划分为在整个研究区间内保持在欧几里得空间中的集合的集合。我们首先将此方法应用于分析地球物理系统，以确定产生鲁棒簇的程序并确定适用于模糊C均值分析的系统的特征。该方法的一个挑战是聚类结果的初始种子依赖性，这需要多种实现来确认鲁棒性。与谱聚类方法的直接比较说明了将模糊C均值方法应用于具有大量相干结构的系统的局限性。然后，我们将程序应用于地球物理流体动力学数值模拟，以可视化显示运输的主要机理。

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