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p>This paper proposes a model of evidential network based on Hybrid Dezert-Smarandache theory (DSmH)br /> to improve target identi cation of multi-sensors. In the classi cation simulation, we compared thebr /> results obtained at the Target Type node and Foe-Ally node in evidential network by using Dempster-br /> Shafer theory (DS) and using DSmH. The comparisons show that, when we use DSmH in the evidentialbr /> network, we can assign more Basic Belief Assignments (BBA) to the focal element the target belongs to.br /> Experiments con rm that the model of evidential network using DSmH is better than the one using DS./p>
Basic Belief Assignments, Evidential Network, Hybrid Dezert-Smarandache theory, Hybrid Dezert-Smarandache theory , Transferable Belief Model (TBM), Basic Belief Assignments, evidential network
Basic Belief Assignments, Evidential Network, Hybrid Dezert-Smarandache theory, Hybrid Dezert-Smarandache theory , Transferable Belief Model (TBM), Basic Belief Assignments, evidential network
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