• DocumentCode
    2024412
  • Title

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

  • Author

    Johannesson, Gardar ; Dyer, Kathleen M. ; Hanley, William G. ; Kosovic, Branko ; Larsen, Shawn C. ; Loosmore, Gwendolen A. ; Lundquist, Julie K. ; Mirin, Arthur A.

  • Author_Institution
    Lawrence Livermore National Laboratory, Livermore, CA, USA
  • fYear
    2006
  • fDate
    13-15 Sept. 2006
  • Firstpage
    144
  • Lastpage
    147
  • Abstract
    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.
  • Keywords
    Atmosphere; Atmospheric modeling; Bayesian methods; Biological system modeling; Chemical processes; Hazardous materials; Laboratories; Monte Carlo methods; Predictive models; Sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nonlinear Statistical Signal Processing Workshop, 2006 IEEE
  • Conference_Location
    Cambridge, UK
  • Print_ISBN
    978-1-4244-0581-7
  • Electronic_ISBN
    978-1-4244-0581-7
  • Type

    conf

  • DOI
    10.1109/NSSPW.2006.4378840
  • Filename
    4378840
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2024412