期刊文献+

基于时间换算的动态证据组合规则

Dynamic evidence combination rules based on time conversion
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摘要 证据理论在解决多源信息融合问题、尤其是不确定性问题上有独到之处.但证据理论组合规则中对动态证据的权威性问题未进行详细地量化,使得动态证据组合过程中产生偏差甚至导致预测结果与人类思维相反.针对上述不足,提出基于时间换算的动态证据组合规则,即将时间换算函数与证据组合规则有机结合起来,可有效地解决动态证据组合过程中产生的偏差,在组合时考虑证据权威的时变性.为验证其有效性,将其用于丰满电厂主变压器故障预测,试验结果支持了该方法. Evidence theory shows special function especially solving uncertainty problem. However, in solving fusion problem of multi-source information and the authoritativeness of dynamic evidence is not analyzed in evidence theory combination rules, which will generate the deviation in the process of dynamic evidence combination, and even induce the prediction opposite to thought of humanity. For the above-mentioned deficiency, the dynamic evidence combination rules based on time conversion has been proposed. Through considering time-varying nature of evidence authoritativeness and combining time conversion function with evidence combination rules, the deviation generated in the process of dynamic evidence combination can be effectively avoided. To testify its effectiveness, the scheme was applied to the trouble detecting of main transformer in Fengman Electricity Generating Station. The test results show that the proposed method is feasible and efficacious.
出处 《沈阳工业大学学报》 EI CAS 2007年第4期435-437,共3页 Journal of Shenyang University of Technology
基金 沈阳工业大学博士启动基金资助项目(521101302)
关键词 信息融合 DEMPSTER-SHAFER理论 时间转换函数 证据组合 故障预测 information fusion Dempster-Shafer theory time conversion function evidence combination trouble prediction
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参考文献9

  • 1Dempster A.Upper and lower probabilities induced by multi-valued mapping[J].Annals of Mathematical Statistics,1967,38 (2):325-339.
  • 2Shafer G.A mathematical theory of evidence[M].Princeton:Princeton University Press,1976.
  • 3Yager R.Using approximate reasoning to represet default knowledge[J].Artificial Intelligence,1987,31(1):99-112.
  • 4Dubois D,Prade H.Default reasoning and possibility theory[J].Artificial Intelligence,1988,35 (2):243 -257.
  • 5Murphy,Robin R.Adaptive rule of combination for observations over time[A].IEEE International Conference on Multi-sensor Fusion and Integration for Intelligent Systems 1996[C].IEEE,Piscataway,NJ,USA,1996:125-131.
  • 6Xia Y,Iyengar S S,Brener N E.Event driven integration reasoning scheme for handling dynamic threats in an unstructured environment[J].Artificial Intelligence,1997,95(1):169-186.
  • 7王壮,胡卫东,郁文贤,庄钊文.基于均衡信度分配准则的冲突证据组合方法[J].电子学报,2001,29(z1):1852-1855. 被引量:18
  • 8孙全,叶秀清,顾伟康.一种新的基于证据理论的合成公式[J].电子学报,2000,28(8):116-119. 被引量:444
  • 9宫义山,赵海,哈铁军,张永庆,徐峰.多源信息的模糊决策树融合算法研究[J].沈阳工业大学学报,2006,28(2):127-131. 被引量:3

二级参考文献22

  • 1谢彦红,杨理践,王向东.基于小波分析的管道缺陷量化识别研究[J].沈阳工业大学学报,2005,27(6):648-651. 被引量:6
  • 2[1]Ronald R.Yager.On the dempster-shafer framework and new combination rules[J].Information Sciences,1987,41:93-137.
  • 3[2]G.Shafer.A mathematical theory of evidence[M].Princeton U.P.,Princeton,1976.
  • 4[3]A.P.Dempster.Upper and lower probabilities induced by a multi-valued mapping[J].Ann.Math.Statist.1967,38:325-339.
  • 5[1]Zadeh.A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination [J].AI Magazinge,1986:85-90.
  • 6[2]P Smets.The combination of evidence in the transferable belief model[J].IEEE Trans.on Pattern Analysis and Machine Intelligence,1990,12(5):447-458.
  • 7[3]G Shafer,R logan.Implementing Dempster's rule for hierarchical evidence [J].Artificial Intelligence,1987,33:271-298.
  • 8[4]R R Yager.On the Dempster-Shafer framework and new combination rules [J].Information Sciences,1987,41:93-138.
  • 9[5]D Dubois,H Prade.Represent and combination of uncertainty with belief functions and possibility measures [J].Comput.Intelll.1988,4:244-264.
  • 10[6]E Levre,O Colot,et al.A generic framework for resolving the conflict in the combination of belief structures [A] .The 3rd International Conference on Information Fusion,July 2000,Paris,France.

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