基于粗糙聚类的稀疏不完整弹道数据有限时间相干集提取方法
A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data
摘要：
我们提出了一种数值方法，以确定区域的相空间，近似保留在一个移动的紧凑的邻域在有限的时间内。我们的方法是基于轨迹数据的时空聚类。该方法的主要优点是能够产生有用的结果，（i）当有相对较少的轨迹和（ii）当有差距的轨迹观察，可以发生与真实数据。该方法易于实现，适用于任何维度，并且运行速度快。
英文摘要：
We present a numerical method to identify regions of phase space that are approximately retained in a mobile compact neighbourhood over a finite time duration. Our approach is based on spatio-temporal clustering of trajectory data. The main advantages of the approach are the ability to produce useful results (i) when there are relatively few trajectories and (ii) when there are gaps in observation of the trajectories as can occur with real data. The method is easy to implement, works in any dimension, and is fast to run.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
