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基于证据融合理论的煤矿顶板安全评价模型 被引量:14

Model for safety evaluation of coal mine roof based on evidence fusion theory
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摘要 针对顶板监测数据来源的复杂性及不确定性,由各监测系统的传感器获得不同信息,根据设定的阈值产生对顶板安全状态的度量,通过构造的基本概率分布函数,对所有的命题赋予一个可信度,应用基于Dempster-Shafer证据理论的合成法则进行多证据融合后,即可凸显顶板安全状态。通过与历史数据对比分析,发现该模型能显著降低监测系统的虚警率,提高顶板安全状态判定的准确性。 Aiming at the complexity and uncertainty of mine roof monitoring data source,the sensors of monitoring system got different information and the measure of roof safety according to the pre-set threshold values,assigned a reliability for all propositions by constructing the basic probability distribution function.After multi-evidence amalgamation that applied combination rule of Dempster-Shafer evidence theory,it showed the mine roof safety status.Historical data analysis proves that the model can significantly reduce the roof safety monitoring system probability of false alarm,and increase the accuracy of determining the roof safety status.
出处 《煤炭学报》 EI CAS CSCD 北大核心 2010年第9期1496-1500,共5页 Journal of China Coal Society
基金 国家高技术研究发展计划(863)资助项目(2009AA062704) 山东省科技攻关项目(2009GG10001004) 矿山灾害预防控制教育部重点实验室开放基金资助项目(MDPC0808)
关键词 证据理论 信息融合 顶板安全 评价模型 D-S evidence theory information fusion roof safety evaluation model
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参考文献13

  • 1Smets P. Imperfect information:imprecision uncertainty, uncertainty management in information systems from needs to solutions [ M ]. Netherlands : Kluwer Academic Publishers, 1997:225-254.
  • 2Lawrence A Klein.多传感器数据融合理论及应用[M].戴亚平,译.北京:北京理工大学出版社,2004.
  • 3Dubois H. Representation and combination of uncertainty with belief functions and possibility measures[J]. Computational Intelligence, 1998( 1 ) :88-101.
  • 4Catherine K Murphy. Combining belief functions when evidence conflicts[J].Decision Support Systems,2000,29 ( 1 ) : 1-9.
  • 5Yager. Research on the Dempster-Shafer framework and new combination rules [J]. IEEE Trans. on System, 1989,41 (2) :93-137.
  • 6贾瑞生,孙红梅,吕英英,杨建英.顶板安全监测数据集成平台的设计与研究[J].计算机测量与控制,2009,17(1):203-206. 被引量:3
  • 7蓝金辉,马宝华,蓝天,周兆英.D-S证据理论数据融合方法在目标识别中的应用[J].清华大学学报(自然科学版),2001,41(2):53-55. 被引量:79
  • 8李丽,程久龙.基于信息融合的矿井底板突水预测[J].煤炭学报,2006,31(5):623-626. 被引量:40
  • 9Mitzias D A, Mertzois B G. A neural multi-classifier system for object recognition in robotic vision applications[J].Measurement, 2004,36(4) :315-330.
  • 10Yella S, Guta N K, Doughertym S. Comparison of pattern recognition techniques for the classification of impact acoustic emissions [ J ]. Trans. Research Part C,2007,15 ( 3 ) :324-335.

二级参考文献21

  • 1马国清,赵亮,李鹏.基于Dempster-Shafer证据推理的多传感器信息融合技术及应用[J].现代电子技术,2003,26(19):41-44. 被引量:16
  • 2李军,于守谦,刘亚斌.基于软件总线技术的测控系统框架实现[J].计算机测量与控制,2005,13(8):849-850. 被引量:10
  • 3潘震中.多传感器信息融合的谢佛-登普斯特方法[J].火力与指挥控制,1994,19(3):12-16.
  • 4Fernando de Ferreira Rezende, Hermsen U. A Practical Approach to Access Heterogeneous and Distributed Databases[A]. Proceedings of the 11th Conference on Advanced Information Systems Engineering [C]. 1999. 6.
  • 5Sheth A P, Larson J A. Federated database systems for managing distributed, heterogeneous, and autonomous database [J]. ACM Computing Surveys, 1990, 9, 22 (3).
  • 6OPC Task Force, OPC Common Definitions and Interfaces Version 1.0 [S]. October 27, 1998.
  • 7OPC Foundation. OPC Data Access Custom Interface Standard Version 3.00 [S]. March 4, 2003.
  • 8http: //en. wikipedia.org/wiki/Dynamic _ Data _ Exchange [EB/OL]. 2007. 12.26.
  • 9潘震中,火力与指挥控制,1994年,19卷,3期,12页
  • 10刘同明 夏祖勋 解洪成.数据融合技术及应用[M].北京:国防工业出版社,1998.1-2.

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