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水文特性参数的证据统计推断方法 被引量:2

An evidential statistical inference method of hydrologic characteristic parameters
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摘要 描述水文现象的随机性的概率分布密度函数中的参数作为证据不确定性,在对这些参数根据观测数据用统计方法估计的基础上,用Dempster_Shafer证据理论的协调性原理对这些不确定参数的真实取值进行推断,确定其真实值在某个可能范围的基本信任度、信任度和不可排除度.推断结果表明,水文特征参数的真实可信值不一定是用统计方法得到的估计值. The parameters,considered as evidence uncertainty, in the probability density function which describes the stochasticism of hydrologic phenomenon are inferred by the consonance principle in Dempster_Shafer theory of evidence,by which basic belief,belief, and the extent of failure to doubt (pausible extent) of possible ranges in which the true values of the parmeters are fallen, calculated and inferred. The inferred results from a set of observed hydrologic data demonstrate that the true believable values of the parameters need not have been the estimated values by statistical methodology.
出处 《武汉大学学报(工学版)》 CAS CSCD 北大核心 2003年第1期32-36,共5页 Engineering Journal of Wuhan University
基金 国家自然科学基金资助项目(6987049 60274048)
关键词 水文学 水文参数 DEMPSTER-SHAFER证据理论 协调性原理 hydrology hydrologic parameter Dempster_Shafer theory of evidence consonance principle evidential statistical inference
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  • 1Yang Jianbo,IEEE SMC,1994年,24卷,1期,1页

同被引文献12

  • 1王线朋.浅谈水文特征的频率及计算[J].河南水利与南水北调,1999,0(1):44-44. 被引量:2
  • 2邓超,郭茂祖.基于自适应数据剪辑策略的Tri-training算法[J].计算机学报,2007,30(8):1213-1226. 被引量:15
  • 3Zhou Zhihua, Li Ming. Tri-training: Exploiting unlabeled data using three clasSifiers[J]. IEEE Trans on Knowledge and Data Engineering, 2005, 17(11): 1529-1541.
  • 4王珏,周志华,周傲英.机器学习及其应用[M].北京:清华大学出版社,2007:259-275.
  • 5Li Ming, Zhou Zhihua. SETRED: Self-training with editing[C]. Proc of the 9th Pacific-Asia Conf on Knowledge Discovery and Data Mining. Hanoi: Springer, 2005:611-621.
  • 6Wang Wei, Zhou Zhihua. Analyzing co-training style algorithms [C]. Proc of the 18th European Conf on Machine Learning. Warsaw, 2007: 454-465.
  • 7Nadeau C, Bengio Y. Inference for the generalization error[J]. Machine Learning, 2003, 52(3): 239-281.
  • 8David R Anderson, Dennis J Sweeney. Statistics for business and economics[M]. Beijing: China Machine Press, 2010: 32%330.).
  • 9Dymitr Rata, Bogdan Gabrys. An overview of classifier fusion methods[J]. Computing and Information Systems, 2000, 7(1): 1-10.
  • 10Xiao-liang Tang, Min Hart. Ternary reversible extreme learning machines: The incremental tri-training method for semi-supervised classification[J]. Knowledge and Information Systems, 2010, 23(3): 345-372.

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