Spatio-temporal modeling of the topology of swarm behavior with persistence landscapes

Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385 and Jones, Christopher Bernard ORCID: https://orcid.org/0000-0001-6847-7575 2016. Spatio-temporal modeling of the topology of swarm behavior with persistence landscapes. Presented at: ACM - SIGSPATIAL 2016, Burlingame, CA, USA, 31 October - 3 November 2016. GIS '16 Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY.: ACM, 10.1145/2996913.2996949

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Abstract

We propose a method for modeling the topology of swarm behavior in a manner which facilitates the application of machine learning techniques such as clustering. This is achieved by modeling the persistence of topological features, such as connected components and holes, of the swarm with respect to time using zig-zag persistent homology. The output of this model is subsequently transformed into a representation known as a persistence landscape. This representation forms a vector space and therefore facilitates the application of machine learning techniques. The proposed model is validated using a real data set corresponding to a swarm of 300 fish. We demonstrate that it may be used to perform clustering of swarm behavior with respect to topological features.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Additional Information:	Article 65
Publisher:	ACM
ISBN:	978-1-4503-4589-7
Date of First Compliant Deposit:	29 September 2016
Date of Acceptance:	28 August 2017
Last Modified:	01 Nov 2022 11:26
URI:	https://orca.cardiff.ac.uk/id/eprint/94932

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