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信任函数逼近方法的改进 被引量：1

The Improvement of Belief Function's Approximations
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摘要 信任函数的逼近可使得不确定性推理理论得以实际应用,该文讨论了D-S证据理论中信任函数逼近的几种方法,分析了它们各自的优缺点,并通过对概括逼近、双逼近和内外聚类逼近的研究,提出了两种新的逼近方法,既满足最佳逼近基本条件要求又考虑了精度要求和计算时间. The approximation of Belief function will make various theories about imprecise probabilities into practice. This article comes up with several kinds of approxiations of Belief function in the D-S theory and discusses the advantage and disadvantage about these approximations. Researching for Summarization, Pair approximation and Inner and Outer clustering approximation, two new approximations are proposed. The two methods satisfied the basic condition of optimal approximation and consider the require of accuracy and time cost.
作者 黄林颖 吴根秀 万宇文 李玮
机构地区 江西师范大学计算机信息工程学院 江西师范大学数学与信息科学学院
出处 《江西师范大学学报（自然科学版）》 CAS 北大核心 2006年第1期58-62,共5页 Journal of Jiangxi Normal University(Natural Science Edition)
基金 国家自然科学基金(60263005) 江西省自然科学基金(0411021) 江西省教育厅2005年资助项目
关键词 证据理论 概括逼近 双逼近 内外聚类逼近 evidence theory pair approximation summarization inner and outer clustering
分类号 TP301 [自动化与计算机技术—计算机系统结构]
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参考文献6

  • 1Voorbraak F.A computationally efficient approximation of dampster-shafer theory[ J].International Journal of Man-Machine Studies,1989,30(5):525-536.
  • 2Enric HernandeZ,Jordi Recasens.Indistinguishability relations in Dempster-Shafer theory of evidence[ J].International Journal of Approximate Reasoning,2004,37(3):145-187.
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  • 5Thierry Denceux.Inner and outer approximation of belief structures using a hierarchical clustering approach[ J].International Journal of Uncertainty,2001,9(4):437-460.
  • 6吴根秀,唐小娟,俞宗火,郑雄军.信任函数的逼近[J].南昌大学学报（理科版）,2004,28(4):345-348. 被引量：1

二级参考文献5

  • 1Lowrance J D,Garvey T D and Strat T M.A Framework for Evidential-reasoning System[A].Int.Kehler,S.Rosenschein R.Filman,and P.F.Patel-Schneider,editors,Proceedings of the 5th National Conference of the American Association for Areifical Intelligence(AAAI-86)[C] .1986(2).896-903.
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  • 3G.shafer A Mathematical Theory of Evidence Princeton[M].University Press Princeton,New Jersey,1976.
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同被引文献13

  • 1Smets P, Kennes R. The transferable belief model [ J ]. Ar- tifial Intelligence, 1994,66 (2) : 191-234.
  • 2Sudano J J. The system probability information content (PIC) relationship to contributing components, combini- ng independent multi-source beliefs, hybrid and pedig-ree pignistic probabilities [ C ]///2002 Proceedings of the Fifth International Conference on Information Fusion. IEEE, 2002 : 1277-1283.
  • 3Sudano J. Pignistic probability transforms for mixes of low- and high-probability events [ J ]. Proc of Fusion, 2001, 2001:23-27.
  • 4Dezert J, Smarandache F. A new probabilistic transforma- tion of belief mass assignment [ C ]//2008 11th Interna- tional Conference on Information Fusion. IEEE ,2008:1-8.
  • 5Sudano J, Martin L. Equivalence between belief theories and naive Bayesian fusion for systems with independent evidential data-Part I, the theory [ J ]. Proc of Fusion, 2003,2003:1239-1243.
  • 6Sudano J J, Martin L. Yet another paradigm illustrating ev- idence fusion ( YAPIEF ) [ C ] //2006 9th International Conference on Information Fusion. IEEE ,2006 : 1-7.
  • 7Cuzzolin F. On the properties of the Intersection proba-Bil- ity [J]. Submitted to the Annals of Mathematics and AI, 2007 ( 1 ) : 1-34.
  • 8Han Deqiang, Dezert J, Han Chongzhao, et al. Is entropy e- nough to evaluate the probability transformation approach of belief function? [ C]//Proc of International Conference on Information Fusion. IEEE ,2010 : 1-7.
  • 9Zhou Zhe, Yang Chunjie, Wen Chenglin. Belief function to probability:A tradeoff between easy decision-making and high risk [C]//2013 lOth IEEE International Conference on Control and Automation (ICCA). IEEE, 2013 : 233- 237.
  • 10蒋雯,吴翠翠,贾佳,李珍键.D-S证据理论中的基本概率赋值转换概率方法研究[J].西北工业大学学报,2013,31(2):295-299. 被引量：15

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二级引证文献4

江西师范大学学报（自然科学版）
2006年 第1期

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