The BNMA BN Repository

This repository is a resource for posting and downloading Bayesian network models for sharing with others and for providing supporting material for publications. Please respect authors' rights where noted.

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4 BNs found.

Ruth_3D

A Bayesian Network (BN) model of female rib cage size and quantified categories of body habitus as presented in the article Development of populational female thorax sizes and body habitus categories using computed tomography (CT) images - ScienceDirect. This is a retrospective analysis of 347 female CT chest axial scans was retrieved from an open access database to establish female rib cage sizes. The model structure specification was determined by following the novel sampling-subject-oriented approach (10.31235/osf.io/gqud3). The classification into three body types was derived from a Multiple Correspondence Analysis performed in R, and the resulting classifications were used as one of the variables in the development of the BN model.

John Xie
Netica .dne format
SpiegelhalterDLC93

A 20 node example of a belief net for medical diagnosis. This file does not contain the numerical probabilities (except those few given in the paper). This, together with the paper, provide a good worked out example for clique tree (i.e. join tree) compiling and propagation.

Paper link: <www.norsys.com...>

Norsys Software Corp
Netica .dne format
Spiegelhalter, D.J., Dawid, A.P., Lauritzen, S.L. & Cowell, R.G. (1993) Bayesian Analysis in Expert Systems. Statist. Sci., 8(3):219-247, The Institute of Mathematical Statistics
Illgraben Decision Graph

The Decision Graph is applied for the assessment and optimization of an existing threshold-based debris flow warning system. To model the warning system and compute the technical and inherent reliability, the Bayesian Network, which is the Decision Graph without the utility node, can be applied alone. Paper: <www.era.bgu.tum.de...>.

Martina Sättele, Michael Bründl, Daniel Straub
GeNIe 2.0 XML format
Fuel Breaks

The model examines the role of the landscape, fuel load, fuel moisture and fuel breaks on changing the risk to property in San Diego County, USA.

Trent Penman
GeNIe 2.0 XML format
Penman, T., Collins, L., Syphard, A.D., Keeley, J.E. & Bradstock, R. (in press) Influence of fuels, weather and the built environment on the exposure of property to wildfire.. PLoS ONE, Accepted 12 September 2014