Abstract
These last years, a lot of combination rules emerged in order to model the situations of belief fusion. These rules can be classified in two different classes. However, these rules do not differentiate between focal elements in the combination step which produce counterintuitive results in some situations. Motivated by this observation, we propose a new combination rule which hybrids the strategies of these two classes. Our rule is two-step operator where the averaging step comes first, and then the conflict redistribution step. Experimental studies are conducted on a real smart home dataset to show the accuracy of our rule in ubiquitous-assisted living situation.
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Sebbak, F., Benhammadi, F., Bouznad, S., Chibani, A., Amirat, Y. (2014). An Evidential Fusion Rule for Ambient Intelligence for Activity Recognition. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_39
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DOI: https://doi.org/10.1007/978-3-319-11191-9_39
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11190-2
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