Cluster-based Specification Techniques in Dempster-Shafer Theory for an Evidential Intelligence Analysis of MultipleTarget Tracks (Thesis Abstract)
Artificial Intelligence
2007-05-23 v1 Neural and Evolutionary Computing
Abstract
In Intelligence Analysis it is of vital importance to manage uncertainty. Intelligence data is almost always uncertain and incomplete, making it necessary to reason and taking decisions under uncertainty. One way to manage the uncertainty in Intelligence Analysis is Dempster-Shafer Theory. This thesis contains five results regarding multiple target tracks and intelligence specification.
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Cite
@article{arxiv.cs/0305018,
title = {Cluster-based Specification Techniques in Dempster-Shafer Theory for an Evidential Intelligence Analysis of MultipleTarget Tracks (Thesis Abstract)},
author = {Johan Schubert},
journal= {arXiv preprint arXiv:cs/0305018},
year = {2007}
}
Comments
4 pages, 1 figure