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信任函数的逼近 被引量:1

THE IMPROVEMENT OF BELIEF FUNCTIONS' APPROXIMATIONS
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摘要 为了解决各种不精确概率理论难以实际应用的问题,于是信任函数的逼近被提出和研究。Lowrance,etal和DavidHarmanec分别提出了信任函数概括逼近法和信任函数的五种启发式计算方法,但这些方法都未能兼顾精度要求和计算速度。本文在比较双逼近法和概括逼近法的优缺点的基础上,给出两种即兼顾精度要求又考虑计算时间的逼近方法。 In order to solve the problem that various theories about imprecise probabilities are applied difficultly,Lowrance.et al and David Harmanec presented belief function's summarization and its five heuristic methods respectively.But these methods cannot balance between the demands of accuracy and computing speed.Comparing the advantages and disadvantages of pair approximation and summarization,this article come up with two kinds of methods which cost less time than pair approximation and have higher accuracy than summarization.
出处 《南昌大学学报(理科版)》 CAS 北大核心 2004年第4期345-348,共4页 Journal of Nanchang University(Natural Science)
基金 江西省自然科学基金项目(0311041)
关键词 证据理论 双逼近 概括逼近 evidence theory pair approximation summarization
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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.
  • 2David Harmanec.Faithful Approximations of Belief Functions[M].National University of Singaport,1999.
  • 3G.shafer A Mathematical Theory of Evidence Princeton[M].University Press Princeton,New Jersey,1976.
  • 4Voorbraak F.A Computationally Efficient Approximation of Dampster-Shafer Theory[J].International Journal of man-Machine Studies,1989,30:525-536.
  • 5Bauer M.Approximations for Decision Making in the Dempster-Shafer Theory of Evidence[M].Uncertainty in Artificial Intelligence(UAI-96),San Francisco,California,Morgan Kanfmann,1996.73-80.

同被引文献5

  • 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.
  • 3Tessem B.Approximations for efficient computation in the theory of evidence[ J ].Artificial Intelligence,1993,61 (2):315-329.
  • 4David Harmanec.Faithful approximations of belief functions[ C].San Francisco:Morgan Kaufman Publishers,1999.
  • 5Thierry Denceux.Inner and outer approximation of belief structures using a hierarchical clustering approach[ J].International Journal of Uncertainty,2001,9(4):437-460.

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