Super Base Station Fault Detection Mechanism Based on Negative Selection Algorithm and Expert Knowledge Base

摘要：

　　With the expansion of network scale and the increase of equipment complexity,the super base station business data has experienced explosive growth,which makes fault detection more and more difficult,and the efficiency of fault management is getting lower and lower.To solve the above problems,this paper designs a comprehensive fault detection mechanism(NSAEFD)by combining the negative selection algorithm in the field of artificial immunity and expert system.NSAEFD is further introduced in detail in super base station(SBS).NSAEFD is also easy to implement and can be well applied to the fault management system of the SBS.

作者: Guanwen Ye Yuanyuan Wang Qian Sun

作者单位: Chongqing University of Posts and Telecommunications,Chongqing,China;Institute of Computing Technolo Institute of Computing Technology,Chinese Academy of Sciences,Beijing,China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Application of Materials Science and Energy Materials (SAMSE 2018) 第二届材料科学应用与能源材料国际研讨会2018年

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2018-12-17（万方平台首次上网日期，不代表论文的发表时间）