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Volume 39 Issue 1
Jan.  2013
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Journal of Beijing University of Aeronautics and Astronautics  > 2013  >  (1): 109-114.
Zhou Fang, Wang Pengbo, Han Liyanet al. Multi-source knowledge fusion algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, (1): 109-114. (in Chinese)
Citation: Zhou Fang, Wang Pengbo, Han Liyanet al. Multi-source knowledge fusion algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, (1): 109-114. (in Chinese)
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Multi-source knowledge fusion algorithm

  • 1.

    Trade Union Committee, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • 2. School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • 3. School of Economics and Management, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 02 Nov 2012
  • Publish Date: 31 Jan 2013
    Abstract
  • Multiple source knowledge fusion can effectively enhance the reliability and credibility of the ruling result. In the light of information fusion, methods and general model of knowledge fusion were analyzed, with emphasis on knowledge fusion algorithms based on Bayes rule, Dempster-Shafer(D-S) proof theory and fuzzy sets theory. Explicit processing steps of the algorithms mentioned above were presented, and comparison between which from the perspectives of the characteristics, applicability wend practicability were drawn as well. Finally, the knowledge fusion algorithms based on Bayes theory was introduced into the field of synthetic aperture radar(SAR) image fusions. Simulation results show the effectiveness of the multiple source knowledge fusion algorithms.

     

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