Structure evolution of dynamic Bayesian network for traffic accident detection

Ju Won Hwang, Young Seol Lee, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Recently, Bayesian network has been widely used to cope with the uncertainty of real world in the field of artificial intelligence. Dynamic Bayesian network, a kind of Bayesian network, can solve problems in dynamic environments. However, as node and state values of node in Bayesian network grow, it is very difficult to define structure and parameter of Bayesian network. This paper proposes a method which generates and evolves structure of dynamic Bayesian network to deal with uncertainty and dynamic properties in real world using genetic algorithm. Effectiveness of the generated structure of dynamic Bayesian network is evaluated in terms of evolution process and the accuracy in a domain of the traffic accident detection.

Original languageEnglish
Title of host publication2011 IEEE Congress of Evolutionary Computation, CEC 2011
Pages1665-1671
Number of pages7
DOIs
Publication statusPublished - 2011 Aug 29
Event2011 IEEE Congress of Evolutionary Computation, CEC 2011 - New Orleans, LA, United States
Duration: 2011 Jun 52011 Jun 8

Publication series

Name2011 IEEE Congress of Evolutionary Computation, CEC 2011

Other

Other2011 IEEE Congress of Evolutionary Computation, CEC 2011
CountryUnited States
CityNew Orleans, LA
Period11/6/511/6/8

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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  • Cite this

    Hwang, J. W., Lee, Y. S., & Cho, S. B. (2011). Structure evolution of dynamic Bayesian network for traffic accident detection. In 2011 IEEE Congress of Evolutionary Computation, CEC 2011 (pp. 1665-1671). [5949815] (2011 IEEE Congress of Evolutionary Computation, CEC 2011). https://doi.org/10.1109/CEC.2011.5949815