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In this paper, we present two novel methods to handle the fusion of multiple Bayesian Network knowledge fragments which we termed N-Combinator and N-Clone. In DSO National Laboratories, we have developed a cognition based dynamic reasoning machine called D'Brain capable of performing high level data fusion. Knowledge is encapsulated in D'Brain as Bayesian Networks knowledge fragments. D'Brain is dynamic...
This paper examines the ordering of measurement updates for a general Bayesian inference problem and its impact on the estimation of the posterior distribution. The approach used compares the expected improvement to the posterior from various types of potential measurements, taking into account the current estimated prior but not the actual measurements, to determine the optimal measurement to perform...
Data fusion within the evidential reasoning framework is a well established, robust and conservative technique to fuse uncertain information from multiple sensors. A number of fusion methods within this formalism were introduced including Dempster-Shafer theory (DST) fusion, Dezert Samarandche fusion (DSmT), and Smets' transferable belief model (TBM) based fusion. However, the impact of fusion on...
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