English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

As mobile networks grow in size and complexity, huge streams of alarms are flooding the operation and maintenance center (OMC). Thus, the operator needs a decision support system that converts these massive alarms to manageable magnitudes. Alarm correlation is very important in improving the service and the efficiency of the maintenance team in mobile networks and in modern telecommunications networks. As any fault in the mobile network results in a number of alarms, correlating these different alarms and identifying their source are a major problem in fault management. In this paper, an artificial neural network model is proposed to interpret the alarm stream, thereby simplifying the decision-making process and shortening the operator's reaction time. MATLAB program is used as programming tool to develop, implement, and compare between different types of designed artificial neural network models. To assist the operators to take fast decision and detect the root cause of the alarms, the alarms and the result of the artificial neural networks model are visualized in real time on the Google Earth application.

Decision Support System for Alarm Correlation in GSM Networks Based on Artificial Neural Networks