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Author (up) Yan Wang; Hong Huang; Wei Zhu pdf 
  Title Stochastic source term estimation of HAZMAT releases: algorithms and uncertainty Type Conference Article
  Year 2015 Publication ISCRAM 2015 Conference Proceedings 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015  
  Volume Issue Pages  
  Keywords Bayesian inference; emergency response; hazardous material releases; source term estimation; uncertainty  
  Abstract Source term estimation (STE) of hazardous material (HAZMAT) releases is critical for emergency response. Such problem is usually solved with the aid of atmospheric dispersion modelling and inversion algorithms accompanied with a variety of uncertainty, including uncertainty in atmospheric dispersion models, uncertainty in meteorological data, uncertainty in measurement process and uncertainty in inversion algorithms. Bayesian inference methods provide a unified framework for solving STE problem and quantifying the uncertainty at the same time. In this paper, three stochastic methods for STE, namely Markov chain Monte Carlo (MCMC), sequential Monte Carlo (SMC) and ensemble Kalman filter (EnKF), are compared in accuracy, time consumption as well as the quantification of uncertainty, based on which a kind of flip ambiguity phenomenon caused by various uncertainty in STE problems is pointed out. The advantage of non-Gaussian estimation methods like SMC is emphasized.  
  Address  
  Corporate Author Thesis  
  Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9788271177881 Medium  
  Track Analytical Modelling and Simulation Expedition Conference ISCRAM 2015 Conference Proceedings 12th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1194  
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