A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data

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A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data. / Froyland, Gary; Padberg-Gehle, Kathrin.
in: Chaos, Jahrgang 25, Nr. 8, 087406, 01.08.2015.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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@article{d2e912d77ecd488da76c556d1a69f0e4,
title = "A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data",
abstract = "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.",
keywords = "Mathematics",
author = "Gary Froyland and Kathrin Padberg-Gehle",
year = "2015",
month = aug,
day = "1",
doi = "10.1063/1.4926372",
language = "English",
volume = "25",
journal = "Chaos",
issn = "1054-1500",
publisher = "American Institute of Physics Inc.",
number = "8",

}

RIS

TY - JOUR

T1 - A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data

AU - Froyland, Gary

AU - Padberg-Gehle, Kathrin

PY - 2015/8/1

Y1 - 2015/8/1

N2 - 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.

AB - 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.

KW - Mathematics

UR - http://www.scopus.com/inward/record.url?scp=84937054000&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/34730f23-4222-34fc-90b6-e831aff3d3db/

U2 - 10.1063/1.4926372

DO - 10.1063/1.4926372

M3 - Journal articles

C2 - 26328577

AN - SCOPUS:84937054000

VL - 25

JO - Chaos

JF - Chaos

SN - 1054-1500

IS - 8

M1 - 087406

ER -

DOI