多源知识融合处理算法

周芳; 王鹏波; 韩立岩

多源知识融合处理算法

1.
北京航空航天大学工会, 100191
2. 北京航空航天大学电子信息工程学院, 北京 100191
3. 北京航空航天大学经济管理学院, 北京 100191

详细信息

中图分类号: TN 957
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- 文章访问数: 2020
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- 被引次数: 0
出版历程
- 收稿日期: 2012-11-02
- 网络出版日期: 2013-01-31

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

摘要

摘要: 多源知识融合可有效提高判决结果的可靠性和置信度.借鉴信息融合的思路,分析了知识融合方法和一般模型.重点讨论了基于Bayes准则、基于D-S(Dempster-Shafer)证据理论以及基于模糊集理论的知识融合算法,给出了基于3种知识融合算法的具体处理步骤,并从算法特点和适用性、实用性等方面对3种知识融合算法性能进行了对比分析.通过知识融合在合成孔径雷达(SAR,Synthetic Aperture Radar)图像融合中应用的仿真实验,验证了知识融合算法的有效性.
- 多源知识融合 /
- Bayes准则 /
- D-S证据理论 /
- 模糊集
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.
- knowledge fusion /
- Bayes rule /
- D-S evidence theory /
- fuzzy sets

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参考文献(13)

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