Open Access

Bayesian-Based Methods for the Estimation of the Unknown Model’s Parameters in the Case of the Localization of the Atmospheric Contamination Source


Cite

[1] Bernardo, J. M. & Smith, A. F. M., Bayesian Theory, Wiley, 1994.10.1002/9780470316870Search in Google Scholar

[2] Fujimoto, K., Nakabayashi S., Applying GMDH algorithm to extract rules from examples, Systems Analysis Modelling Simulation, 43, 10, 2003. 1311-1319.10.1080/0232929032000115047Search in Google Scholar

[3] Gelman, A., J. Carlin, H. Stern, and D. Rubin, Bayesian Data Analysis, Chapman & Hall/CRC, 2003.10.1201/9780429258480Search in Google Scholar

[4] Gifford, F. A. Jr. Atmospheric dispersion calculation using generalized Gaussian Plum model, Nuclear Safety, 1960, 2(2):56-59, 67-68.Search in Google Scholar

[5] Gilks, W., S. Richardson, and D. Spiegelhalter, Markov Chain Monte Carlo inPractice. Chapman & Hall/CRC, 1996, 486.10.1201/b14835Search in Google Scholar

[6] Ivakhnenko, A.G., Group method of data Handling - A Rival of the Method of Stochastic Approximation, Soviel Automatic Control, 13, 43-71, 1966.Search in Google Scholar

[7] Johannesson, G. et al., Sequential Monte-Carlo based framework for dynamic datadriven event reconstruction for atmospheric release., Proc. of the Joint StatisticalMeeting, Minneapolis, MN, American Statistical Association and Cosponsors, 2005, 73-80.10.1109/NSSPW.2006.4378840Search in Google Scholar

[8] Johannesson, G., W. Hanley, and J. Nitao, Dynamic Bayesian models via Monte Carlo - An introduction with examples, Lawrence Livermore National Laboratory Tech. Rep., 2004, 53.10.2172/15011532Search in Google Scholar

[9] Keats, A., E. Yee, and F.-S. Lien, Bayesian inference for source determination with applications to a complex urban environment. Atmos. Environ., 41, 2007, 465-479.10.1016/j.atmosenv.2006.08.044Search in Google Scholar

[10] Madala H.R., Ivakhnenko A.G., Inductive Learning Algorithms for Complex SystemsModeling, CRC Press, 1994.Search in Google Scholar

[11] Panofsky, H. A., Dutton, J. A., Atmospheric Turbulence. John Wiley, 1984.Search in Google Scholar

[12] Pasquill, F. The estimate of the dispersion of windborne material, Meteorol Mag.,90, 1063, 1984, 33-49.Search in Google Scholar

[13] Pudykiewicz, J. A., Application of adjoint tracer transport equations for evaluating source parameters. Atmos. Environ., 32, 1998, 3039-3050.10.1016/S1352-2310(97)00480-9Search in Google Scholar

[14] Senocak I., N. W. Hengartner, M. B. Short, W. B. Daniel, Stochastic Event Reconstruction of Atmospheric Contaminant Dispersion Using Bayesian Inference, Atmos. Environ., 42(33) , 2008, 7718-7727.10.1016/j.atmosenv.2008.05.024Search in Google Scholar

[15] Thomson, L. C., Hirst, B., Gibson, G., Gillespie, S., Jonathan, P., Skeldon, K. D., Padgett, M. J., An improved algorithm for locating a gas source using inverse methods. Atmospheric Environment, 41, 2007, 1128-1134.10.1016/j.atmosenv.2006.10.003Search in Google Scholar

[16] Turner D. Bruce, Workbook of Atmospheric Dispersion Estimates, Lewis Publishers, USA,1994.Search in Google Scholar

[17] Vicenç Puiga,Marcin Witczak, Fatiha Nejjari, Joseba Quevedo, Józef Korbicz, A GMDH neural network-based approach to passive robust fault detection using a constraint satisfaction backward test, Engineering Applications of ArtificialIntelligence, 20, Issue 7, 2007, 886-897.10.1016/j.engappai.2006.12.005Search in Google Scholar

[18] Watzenig,D., Bayesian inference for inverse problems - statistical inversion. Elektrotechnik and Informationstechnik ,124/7/8, 2007, 240-247.10.1007/s00502-007-0449-0Search in Google Scholar

eISSN:
2300-3405
ISSN:
0867-6356
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Artificial Intelligence, Software Development