Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Entire DC Network
Application Of A Bayesian Inference Method To Reconstruct Short-Range Atmospheric Dispersion Events, Inanc Senocak
Application Of A Bayesian Inference Method To Reconstruct Short-Range Atmospheric Dispersion Events, Inanc Senocak
Inanc Senocak
In the event of an accidental or intentional release of chemical or biological (CB) agents into the atmosphere, first responders and decision makers need to rapidly locate and characterize the source of dispersion events using limited information from sensor networks. In this study the stochastic event reconstruction tool (SERT) is applied to a subset of the Fusing Sensor Information from Observing Networks (FUSION) Field Trial 2007 (FFT 07) database. The inference in SERT is based on Bayesian inference with Markov chain Monte Carlo (MCMC) sampling. SERT adopts a probability model that takes into account both positive and zero-reading sensors. In …