The Multi-Source Signatures for Nuclear Programs project, part of Pacific Northwest National Laboratory’s (PNNL) Signature Discovery Initiative, seeks to computationally capture expert assessment of multi-type information such as text, sensor output, imagery, or audio/video files, to assess nuclear activities through a series of Bayesian network (BN) models. These models incorporate knowledge from a diverse range of information sources in order to help assess a country’s nuclear activities. The models span engineering topic areas, state-level indicators, and facility-specific characteristics. To illustrate the development, calibration, and use of BN models for multi-source assessment, we present a model that predicts a country’s likelihood to participate in the international nuclear nonproliferation regime. We validate this model by examining the extent to which the model assists non-experts arrive at conclusions similar to those provided by nuclear proliferation experts. We also describe the PNNL-developed software used throughout the lifecycle of the Bayesian network model development.
Revised: September 30, 2013 |
Published: June 4, 2013
Citation
Gastelum Z.N., A.M. White, P.D. Whitney, L.J. Gosink, and L.H. Sego. 2013.The Lifecycle of Bayesian Network Models Developed for Multi-Source Signature Assessment of Nuclear Programs. In IEEE International Conference on Intelligence and Security Informatics (ISI 2013), June 4-7, 2013, Seattle, Washington, edited by K Glass, et al, 339-345. Piscataway, New Jersey:IEEE.PNNL-SA-94497.doi:10.1109/ISI.2013.6578855