• DocumentCode
    2138589
  • Title

    An uncertainty reasoning method based on evidence theory

  • Author

    Yan He ; Caiquan Xiong ; Yifan Zhan

  • Author_Institution
    Sch. of Comput. Sci., Hubei Univ. of Technol., Wuhan, China
  • fYear
    2013
  • fDate
    23-25 July 2013
  • Firstpage
    1021
  • Lastpage
    1025
  • Abstract
    Uncertainty reasoning plays an important role in the inference with incomplete information. This paper presents a simplified uncertainty reasoning model based on evidence theory. This method deals with uncertain premises. A special probability assignment function is proposed to simplify the computation. A probabilistic function is presented to represents the certainty of the conclusion. We can get the probability assignment function which represents all propositions. An example is given for confirming the process of the inference. This method can deal with “ignorance” and “uncertain” information flexibly. The conclusion may be more general so that experts can present their knowledge easily.
  • Keywords
    inference mechanisms; probability; uncertainty handling; evidence theory; ignorance factor; incomplete information; inference process; probabilistic function; probability assignment function; uncertain information; uncertainty reasoning method; Bayes methods; Cognition; Expert systems; Fuzzy reasoning; Probability distribution; Uncertainty; combination rule; evidence theory; uncertainty reasoning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2013 Ninth International Conference on
  • Conference_Location
    Shenyang
  • Type

    conf

  • DOI
    10.1109/ICNC.2013.6818126
  • Filename
    6818126