Abstract. This paper investigates the efficiency of in-door next location prediction by comparing several prediction methods. The scenario concerns people in an office building vis...
Jan Petzold, Andreas Pietzowski, Faruk Bagci, Wolf...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
We develop a multi-objective model for the resource allocation problem in a dynamic PERT network, where the activity durations are exponentially distributed random variables and t...
A hybrid Bayesian Network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment the models are...
Martin Neil, Manesh Tailor, Norman E. Fenton, Davi...