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文章基本信息

  • 标题:A Cascading Neural Network Ensemble for Locating Faults of Large-scale Information Systems
  • 本地全文:下载
  • 作者:Chen Zhifeng ; Peng Minjing ; Li Bo
  • 期刊名称:International Journal of Security and Its Applications
  • 印刷版ISSN:1738-9976
  • 出版年度:2014
  • 卷号:8
  • 期号:5
  • 页码:75-84
  • DOI:10.14257/ijsia.2014.8.5.08
  • 出版社:SERSC
  • 摘要:Failure types of Information Systems are varied, which leads to the long duration for locating faults, and decreases the quality of customer service or income. In order to accurately and timely locating BOSS faults, a cascading neural network ensemble was proposed. In the proposed ensemble, the approach of ensemble was used to promote the accuracy of locating faults, and the cascading structure was employed to decrease the time duration of locating. The proposed approach used in fault location BOSS achieved the following results: (1) the speed of locating faults has been improved; (2) complaint rate from customers has been reduced; (3) the billing losses have been decreased.
  • 关键词:Fault locating; Neural network; Cascading structure; Ensemble; Customer ; service
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