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  • 标题:A new model for threat assessment in data fusion based on fuzzy evidence theory
  • 本地全文:下载
  • 作者:Ehsan Azimirad ; Javad Haddadnia
  • 期刊名称:IJAIN (International Journal of Advances in Intelligent Informatics)
  • 印刷版ISSN:2442-6571
  • 电子版ISSN:2548-3161
  • 出版年度:2016
  • 卷号:2
  • 期号:2
  • 页码:54-64
  • DOI:10.26555/ijain.v2i2.56
  • 语种:English
  • 出版社:Universitas Ahmad Dahlan
  • 摘要:In this paper a new method for threat assessment is proposed based on Fuzzy Evidence Theory. The most widely classical and intelligent methods used for threat assessment systems will be Evidence or Dempster Shafer and Fuzzy Sets Theories. The disadvantage of both methods is failing to calculate of uncertainty in the data from the sensors and the poor reliability of system. To fix this flaw in the system of dynamic targets threat assessment is proposed fuzzy evidence theory as a combination of both Dempster- Shafer and Fuzzy Sets Theories. In this model, the uncertainty in input data from the sensors and the whole system is measured using the best measure of the uncertainty. Also, a comprehensive comparison is done between the uncertainty of fuzzy model and fuzzy- evidence model (proposed method). This method applied to a real time scenario for air threat assessment. The simulation results show that this method is reasonable, effective, accuracy and reliability.
  • 关键词:Threat Assessment;Fuzzy Evidence Theory;Dempster- Shaffer Theory;Imperfect Information;Uncertainty Measures
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