Sequential Monte-Carlo Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release

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The release of hazardous materials into the atmosphere can have a tremendous impact on dense populations. We propose an atmospheric event reconstruction framework that couples observed data and predictive computer-intensive dispersion models via Bayesian methodology. Due to the complexity of the model framework, a sampling-based approach is taken for posterior inference that combines Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) strategies.

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Johannesson, G; Dyer, K; Hanley, W; Kosovic, B; Larsen, S; Loosmore, G et al. July 17, 2006.

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Description

The release of hazardous materials into the atmosphere can have a tremendous impact on dense populations. We propose an atmospheric event reconstruction framework that couples observed data and predictive computer-intensive dispersion models via Bayesian methodology. Due to the complexity of the model framework, a sampling-based approach is taken for posterior inference that combines Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) strategies.

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PDF-file: 6 pages; size: 87.5 Kbytes

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  • Presented at: Nonlinear Statistical Signal Processing Workshop, Cambridge, United Kingdom, Sep 13 - Sep 15, 2006

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  • Report No.: UCRL-PROC-222915
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 893974
  • Archival Resource Key: ark:/67531/metadc878494

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Office of Scientific & Technical Information Technical Reports

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  • July 17, 2006

Added to The UNT Digital Library

  • Sept. 22, 2016, 2:13 a.m.

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  • Dec. 8, 2016, 10:53 p.m.

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Johannesson, G; Dyer, K; Hanley, W; Kosovic, B; Larsen, S; Loosmore, G et al. Sequential Monte-Carlo Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release, article, July 17, 2006; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc878494/: accessed October 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.