Dsmh Evidential Network For Target Identication
Xian Li, Zhigang Chen, Peiliang Jing · Zenodo (CERN European Organization for Nuclear Research) · 2015
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>