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Dsmh Evidential Network For Target Identication

Authors: Xian LI; Zhigang CHEN; Peiliang JING;

Dsmh Evidential Network For Target Identication

Abstract

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>

Keywords

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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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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