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数据挖掘在综合网管告警相关性中的研究与应用

Research and Application of Data Mining in Alarm Relevance of Integrated Network Management
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摘要 随着社会经济的不断进步,我国的电信事业得到了很大的发展,对电信网进行综合化的管理以及让电信网的管理变得更加智能化,也是目前电信网网络管理系统主要发展的方向。综合性的网络管理系统的目标就是能够集中监控多个子网,但是由于目前电信网络的规模逐渐变大且结构也相对比较复杂,在同一时间产生的一些告警信息具有多类型、数量庞大等的特点,要想对告告警的根源进行分析和定位是非常困难的事情,而有效利用好数据挖掘技术能够进一步解决综合网管告警当中存在的问题,让网络的运行更加流畅,质量不断提高。因此本文主要研究了数据挖掘在综合网管告警相关性及其应用,希望能够提供一定的参考价值。 With the continuous progress of social economy,China's telecommunications industry has been greatly developed.Integrated management of telecommunications network and making the management of telecommunications network more intelligent are also the main development direction of telecommunications network manageement system.The goal of a comprehensive network management system is to be able to centrally monitor multiple subnetworks.However,as the scale of the telecommunication network is becoming larger and the structure is relatively complex,some alarm information generated at the same time has the characteristics of many types and large quantities.It is very difficult to analyze and locate the origin of the alarm,and to make good use of the data.Mining technology can further solve the problems existing in the integrated network management alarm,make the network run more smoothly and improve the quality continuously.Therefore,this paper mainly studies the correlation and application of data mining in integrated network management alarm,hoping to provide some reference value.
作者 曹素娥 CAO Su-e(school of Computer and Network Engineering,Shanxi Datong University,Shanxi Datong,037009)
出处 《软件》 2019年第9期135-138,共4页 Software
关键词 数据挖掘 综合管网告警 Data mining Integrated pipeline network warning
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  • 1张锦,成奋华,林雪梅,李睿,王实.基于子图特征组合的人脸识别技术研究[J].湖南大学学报(自然科学版),2007,34(6):70-73. 被引量:7
  • 2YANG M H, KRIEGMAN D J. AHUJA N. Detecting Faces in Images: A Survey[J]. IEEE Trans. On PAMI, 2002, 24(1) :34-58.
  • 3Yang J, Zhang D, Frangi AF, and Yang JY. Two Dimensional PCA: A New Approach to Appearance - Based Face Representation and Recognition[ J ]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2004, 26 ( 1 ) : 131-137.
  • 4Bartlett MS, Lades HM, Sejnowshi T. Face Recognition by Independent Component Analysis[J ]. IEEE Transaction on Neural Networks, 2002, 13(6) : 1450-1464.
  • 5Vapnik V.N. The Nature of Dtatistical Learning Theory[M]. New York: Springer - Verlag, 1995:235-313.
  • 6SAMARIA F S, HARTER A C. Parameterization of a stochastic model for human face identification[C]. Proc. of the Second IEEE Workshop on Applications of Computer Vision. Sarasota, 1994 : 138-142.
  • 7Liu XM, Chen T, Kurnar BVK. Face Authentication for Multiple Subjects Using Eigenflow[J]. Pattern Recognition, 2003, 36(2) :313-328.
  • 8S.Mallat. A theory for Multiresolution signal decomposition.-the wavelet representation. IEEE Trans. PAMI, 1999, 11(7).. 674-693.
  • 9F CHENG, J YU, H XIONG, Facial Expression Recognition in JAFFE Dataset Based on Gaussian Process Classitlcation[J].Neural Networks, IEEE Transactions on,2010,21(10): 1685- 1690.
  • 10X XIE, K.M LAM, Face recognition using elastic local reconstruction based on a single face image[J].Pattem Recognition,2008, 41(1): 406-417.

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