Abstract
The recursive use of belief function combination rules, as required with temporal data, is issue prone. Systems will either become unreactive, through a greedy empty set, or provide a false sense of security through applying a closed world model to an open world scenario. We improve on the previous combination rule GRP1 to enhance its ability to work with temporal data in an open world. Specifically we have progressed with the dynamic self adjustment properties of the rule, which allow it to gauge how fusion should take place dependant on the temporal information that it receives. Comparisons are made between the improved GRP1 rule and other rules which have been applied to temporal datasets.
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© 2012 Springer-Verlag Berlin Heidelberg
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Powell, G., Roberts, M., Stampouli, D. (2012). Improvements to the GRP1 Combination Rule. In: Denoeux, T., Masson, MH. (eds) Belief Functions: Theory and Applications. Advances in Intelligent and Soft Computing, vol 164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29461-7_34
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DOI: https://doi.org/10.1007/978-3-642-29461-7_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29460-0
Online ISBN: 978-3-642-29461-7
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