Deep Fault Prediction with Flexible Weighted Mining Based Alarm Correlation Analysis of Communication Networks

2020 ◽  
Author(s):  
Jun Jia ◽  
Chunyan Feng ◽  
Tiankui Zhang ◽  
Hailun Xia ◽  
Jinling Li ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Communication Networks ◽  
Fault Prediction ◽  
Deep Fault ◽  
Alarm Correlation

A New Algorithm for the Fuzziness of Alarms in Network Faults Diagnosis

2012 ◽  
Vol 198-199 ◽  
pp. 1539-1544 ◽  
Author(s):  
Pan Liu ◽  
Xing Ming Li ◽  
Jian Wu
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Communication Networks ◽  
Association Rules ◽  
Association Rules Mining ◽  
Fuzzy Association Rules ◽  
Edge Field ◽  
Alarm Correlation ◽  
Faults Diagnosis ◽  
Network Fault

The alarm correlation analysis based on fuzzy association rules mining is the popular and cutting-edge field of the network fault diagnosis research. In the application environment of alarms in communication networks, a new algorithm of the fuzziness of alarms which is called FKMA (Fuzzy K-Means of Alarms algorithm) is proposed .During the process of fuzziness, there are two methods of sorting the center. Simulations are carried out to the comparison of the two methods. The fuzziness of alarms is effectively realized. And fuzzy association rules mining are achieved. The advantages and efficiency of FKMA are demonstrated by experiments.

Alarm Correlation Analysis Method Based on Fuzzy Immune Evolution

2014 ◽  
Vol 556-562 ◽  
pp. 6191-6195
Author(s):  
Yong Wei Wang ◽  
Hui Fang Su ◽  
Wei Qiu
Keyword(s):  
Correlation Analysis ◽  
Time Window ◽  
Correlation Method ◽  
Analysis Method ◽  
Selection Algorithm ◽  
Artificial Immune ◽  
Fuzzy Correlation ◽  
Alarm Correlation ◽  
Correlation Analysis Method ◽  
Correlation Rules

This paper proposes a correlation analysis method based on fuzzy rules and artificial immune. Firstly, we adopt the alarms selection algorithm based on a sliding time window to improve the efficiency of selected alarm. Secondly, the analysis method based on fuzzy correlation rules is used to associate the known patterns static and rapidly. Then, using a method based on immune evolution to improve and adaptive the antibody so as to achieve the dynamic, intelligent correlation of unknown model. The experimental results in LLDOS1.0 and LLDOS2.0 show that the new method gets better accuracy than typical correlation methods, which can ensure the efficiency of correlation analysis and the adaptability of the correlation method.

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