Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, bu...
Ulrik Franke, Pontus Johnson, Robert Lagerströ...
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
Research into design rationale in the past has focused on argumentation-based design deliberations. These approaches cannot be used to support change impact analysis effectively ...
Using 802.11 concurrently for communications and positioning is problematic, especially if location-based services (e.g., indoor navigation) are concurrently executed with real-ti...