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定性Dempster-Shafer理论 被引量:2

Symbolic Dempster-Shafer Theory
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摘要 采用一个全序的符号值集合来代替数值信任度集合[0,1],提出定性Dempster-Shafer理论来处理既有不确定性又有不精确性的推理问题·首先,定义了适合对不确定性进行定性表达和推理的定性mass函数、定性信任函数等概念,并且研究了这些概念之间的基本关系;其次,详细讨论了定性证据合成问题,提出了基于平均策略的证据合成规则·这种定性Dempster-Shafer理论与其他相关理论相比,既通过在定性领域重新定义Dempster-Shafer理论的基本概念,继承了Dempster-Shafer理论在不确定推理方面的主要特点,同时又具有适合对不精确性操作的既有严格定义又符合直观特性的定性算子,因此更适合基于Dempster-Shafer理论框架不精确表示和处理不确定性· Symbolic Dempster-Shafer (D-S for short) theory is presented to handling imprecise and uncertain reasoning. The numerical set of belief degrees [ 0,1 ] in classical D-S theory is replaced by a totally ordered scale of symbolic values. After the qualitative mass function and qualitative belief function are defined by qualitative operators, the fundamental relation between them is discussed. The combination of evidence in qualitative way is also discussed in detail. Compared to other related work, there are two essential characteristics of the symbolic D-S theory. One is that the theory inherits the advantages of classic D-S theory on uncertain reasoning by re-defining the essential concepts in D-S theory. Another one is that the qualitative operators involved in the approach are strictly defined by the logic formulas as well as intuitive properties. Consequently, the symbolic D-S theory is more suitable for reasoning about uncertainty and imprecision in the framework of D-S theory.
出处 《计算机研究与发展》 EI CSCD 北大核心 2005年第11期1833-1842,共10页 Journal of Computer Research and Development
基金 国家自然科学基金项目(69925203) 国家自然科学基金重大项目(60496324 60496322)~~
关键词 DEMPSTER-SHAFER理论 不确定性 不精确性 Dempster-Shafer theory uncertainty impreciseness
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参考文献13

  • 1G. Shafer. A Mathematical Theory of Evidence. Princeton:Princeton University Press, 1976.
  • 2J. Pearl. Reasoning with belief functions: An analysis of compatibility. International Journal of Approximate Reasoning,1990, 4(5-6): 363~389.
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  • 4H. Seridi, F. Bannay-Dupin De ST CYR, H. Akdag. Qualitative operators for dealing with uncertainty. In: Proc 5th Int'l Workshop Fuzzy-NeuroSystems. Munich:Infix, 1998. 202~209.
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二级参考文献6

  • 1[1]J Pearl. Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference. San Mateo, CA: Morgan Kaufmann, 1988
  • 2[2]H Akdag, M DeGLas, D Pacholczyk. A qualitative theory of uncertainty. Fundamenta Informaticae, 1992, 17(4): 333~362
  • 3[3]H Seridi, F Bannay-Dupin De ST CYR, H Akdag. Qualitative operators for dealing with uncertainty. In: The 5th Int'l Workshop Fuzzy-Neuro Systems'98. Munich: Infix, 1998. 202~209
  • 4[4]A Chawki Osseiran. Qualitative Bayesian network. Information Sciences, 2001, 131(1-4): 87~106
  • 5[5]L Zadeh. PRUF-A meaning representation language for natural languages. The Int'l Journal of Man-Machine Studies,1978, 10(4): 395~460
  • 6[6]Herman Akdag, Myriam Morhtari. Approximative conjunctions processing by multi-valued logic. In: IEEE Int'l Symp on Multiple-Valued Logic (ISMVL'96). Santiago de Compostela, Spain: IEEE Computer Society, 1996. 130~135

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