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舰船云计算系统服务器故障的识别模型
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  • 英文篇名:Server fault recognition model of ship cloud computing system
  • 作者:王红霞
  • 英文作者:WANG Hong-xia;Baotou Iron and Steel Vocational Technical College;
  • 关键词:舰船云计算系统 ; 服务器故障 ; 识别模型 ; 数据挖掘
  • 英文关键词:warship cloud computing system;;server failure;;identification model;;data mining
  • 中文刊名:JCKX
  • 英文刊名:Ship Science and Technology
  • 机构:包头钢铁职业技术学院;
  • 出版日期:2019-02-23
  • 出版单位:舰船科学技术
  • 年:2019
  • 期:v.41
  • 语种:中文;
  • 页:JCKX201904053
  • 页数:3
  • CN:04
  • ISSN:11-1885/U
  • 分类号:158-160
摘要
舰船云计算系统服务器故障的种类多,故障与特征之间是一种非常复杂的映射关系,传统舰船云计算系统服务器故障识别模型难以获得理想的识别结果。为了克服当前舰船云计算系统服务器故障识别模型存在的不足,设计一种基于数据挖掘的舰船云计算系统服务器故障识别模型。首先采集舰船云计算系统服务器故障识别数据,然后采用数据挖掘技术对舰船云计算系统服务器故障识别数据进行分析和建模,建立舰船云计算系统服务器故障识别的分类器,最后进行了舰船云计算系统服务器故障识别仿真对比实验。本文模型的舰船云计算系统服务器故障识别率高达95%,而且舰船云计算系统服务器故障的误识率要小于当前其他舰船云计算系统服务器故障识别模型,结果验证了本文模型的优越性。
        There are many kinds of server failures in warship cloud computing system, and the mapping relationship between the failures and features is not complex. It is difficult for traditional server fault identification model of warship cloud computing system to obtain ideal recognition results. In order to overcome the shortcomings of current server fault identification model of warship cloud computing system, a server fault identification model of warship cloud computing system based on data mining is designed.. Firstly, the fault identification data of the server of the naval cloud computing system is used, then the fault identification data of the server of the naval cloud computing system is analyzed and modeled by data mining technology, and the classifier of the fault identification of the server of the naval cloud computing system is established. Finally, the comparative simulation experiment of the server fault identification of the naval cloud computing system is carried out. The naval cloud computing system clothing of the model in this paper is based on the The recognition rate of server faults is as high as 95%, and the error recognition rate of server faults in naval cloud computing system is less than that of other current server fault identification models. The results verify the superiority of this model.
引文
[1]雷福宝,马建敏,李晶.基于云计算技术的舰船通信网络路由算法研究[J].舰船科学技术, 2018, 40(22):133–135.
    [2]聂晶.云计算系统服务器节点故障的检测算法[J].内蒙古师范大学学报(自然科学汉文版), 2018, 47(1):23–27, 34.
    [3]谭营军,张铁头,李翠霞.大型云计算多服务器环境下故障节点定位仿真[J].控制工程, 2014, 21(6):909–912.

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