DOI QR코드

DOI QR Code

Design of Time-varying Stochastic Process with Dynamic Bayesian Networks

  • 발행 : 2007.12.31

초록

We present a dynamic Bayesian network (DBN) model of a generalized class of nonstationary birth-death processes. The model includes birth and death rate parameters that are randomly selected from a known discrete set of values. We present an on-line algorithm to obtain optimal estimates of the parameters. We provide a simulation of real-time characterization of load traffic estimation using our DBN approach.

키워드

참고문헌

  1. I. Zeifman, 'General Birth-death processes and simple stochastic epidemic models,' Automation and Remote Control, vol. 46, no. 6, pp. 789-795, 1985
  2. S. Blaabjerg and H. Andersson, 'Approximating the heterogeneous fluid queue with a birth-death fluid queue,' IEEE Trans. on Communications, vol. 43, no. 5, pp. 1884-1887, 1995 https://doi.org/10.1109/26.387416
  3. M. Alonso and F. J. Alguacil, 'Stochastic modeling of particle coating.' AIChE Journal, vol. 47, no. 6, pp. 1303-1308, 2001 https://doi.org/10.1002/aic.690470608
  4. S. C. Kou, 'Modeling growth stocks via birth-death processes,' Advances in Applied Probability, vol. 35, no. 3, pp. 641-664, 2003 https://doi.org/10.1239/aap/1059486822
  5. P. R. Parthasarathy and K. V. Vijayashree, 'Fluid queues driven by birth and death processes with quadratic rates,' International Journal of Computer Mathematics, vol. 80, no. 11, pp. 1385-1395, 2003 https://doi.org/10.1080/0020716031000120836
  6. V. Rykov, 'Generalized birth-death processes and their application to the ageing models,' Automation and Remote Control, vol. 67, no. 3, pp. 435-451, 2006 https://doi.org/10.1134/S0005117906030088
  7. K. Murphy, 'Dynamic Bayesian networks: Representation, Inference and Learning.' Ph.D. Dissertation, UC Berkeley, 2002
  8. J. N. Daigle, Queuing theory with applications to packet telecommunication, New York, Springer, 2005
  9. J. M. Mendel, Lessons in estimation theory for signal processing, communications, and control, New Jersey, Prentice Hall, 1995
  10. W. J. Rugh, Linear system theory, Prentice Hall, 1996
  11. Y.-H. Wen, T-T Lee, and H-J Cho, 'Hybrid Greybased recurrent neural networks for short-term traffic forecasting and dynamic travel time estimation,' IEEE Conference on Intelligent Transportation Systems, 2005

피인용 문헌

  1. Dynamic Bayesian modelling of non-stationary stochastic systems using constrained least square estimation and gradient descent optimisation vol.6, pp.6, 2012, https://doi.org/10.1049/iet-spr.2010.0081
  2. Fault Detection and Isolation of Induction Motors Using Recurrent Neural Networks and Dynamic Bayesian Modeling vol.18, pp.2, 2010, https://doi.org/10.1109/TCST.2009.2020863