Reliable Force Aggregation Using a Refined Evidence Specification from Dempster-Shafer Clustering

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dc.creatorSchubert, Johan
dc.date2003-05-16
dc.date.accessioned2026-07-07T03:19:42Z
dc.date.available2026-07-07T03:19:42Z
dc.descriptionIn this paper we develop methods for selection of templates and use these templates to recluster an already performed Dempster-Shafer clustering taking into account intelligence to template fit during the reclustering phase. By this process the risk of erroneous force aggregation based on some misplace pieces of evidence from the first clustering process is greatly reduced. Finally, a more reliable force aggregation is performed using the result of the second clustering. These steps are taken in order to maintain most of the excellent computational performance of Dempster-Shafer clustering, while at the same time improve on the clustering result by including some higher relations among intelligence reports described by the templates. The new improved algorithm has a computational complexity of O(n**3 log**2 n) compared to O(n**2 log**2 n) of standard Dempster-Shafer clustering using Potts spin mean field theory.
dc.description8 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/cs/0305030
dc.identifierhttp://arxiv.org/abs/cs/0305030
dc.identifierin Proceedings of the Fourth Annual Conference on Information Fusion (FUSION 2001), pp. TuB3/15-22, Montreal, Canada, 7-10 August 2001, International Society of Information Fusion, Sunnyvale, 2001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31566
dc.subjectArtificial Intelligence
dc.subjectNeural and Evolutionary Computing
dc.subjectI.2.3; I.2.6; I.5.3
dc.titleReliable Force Aggregation Using a Refined Evidence Specification from Dempster-Shafer Clustering
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