December 12, 2014-China Academy of Telecommunication Research of MIIT has announced its analysis report of domestic mobile phone market of November 2014. In November 2014, the overall shipments of mobile phones reach...December 12, 2014-China Academy of Telecommunication Research of MIIT has announced its analysis report of domestic mobile phone market of November 2014. In November 2014, the overall shipments of mobile phones reached 44.543 million units in China. Among which 2G mobile phone shipments was of 5.742 million, 3G mobile phone was of 7.2 million and 31.601 million for 4G ones. 4G mobile phone shipments continued to increase rapidly, which was more than 4 times of 3G mobile phone shipments.展开更多
Mobile network operators are facing many challenges to satisfy their subscribers in terms of quality of service and quality of experience provided. To achieve this goal, technological progress and scientific advances ...Mobile network operators are facing many challenges to satisfy their subscribers in terms of quality of service and quality of experience provided. To achieve this goal, technological progress and scientific advances offer good opportunities for efficiency in the management of faults occurring in a mobile network. Machine learning techniques allow systems to learn from past experiences and can predict, solutions to be applied to correct the root cause of a failure. This paper evaluates machine learning techniques and identifies the decision tree as a learning model that provides the most optimal error rate in predicting outages that may occur in a mobile network. Three machine learning techniques are presented in this study and compared with regard to accuracy. This study demonstrates that the appropriate machine learning technique improves the accuracy of the model. By using the decision tree as a machine learning model, it was possible to predict solutions to network failures, with an error rate less than 2%. In addition, the use of Machine Learning makes it possible to eliminate steps in the network failure processing chain;resulting in reduced service disruption time and improved the network availability which is a key network performance index.展开更多
文摘December 12, 2014-China Academy of Telecommunication Research of MIIT has announced its analysis report of domestic mobile phone market of November 2014. In November 2014, the overall shipments of mobile phones reached 44.543 million units in China. Among which 2G mobile phone shipments was of 5.742 million, 3G mobile phone was of 7.2 million and 31.601 million for 4G ones. 4G mobile phone shipments continued to increase rapidly, which was more than 4 times of 3G mobile phone shipments.
文摘Mobile network operators are facing many challenges to satisfy their subscribers in terms of quality of service and quality of experience provided. To achieve this goal, technological progress and scientific advances offer good opportunities for efficiency in the management of faults occurring in a mobile network. Machine learning techniques allow systems to learn from past experiences and can predict, solutions to be applied to correct the root cause of a failure. This paper evaluates machine learning techniques and identifies the decision tree as a learning model that provides the most optimal error rate in predicting outages that may occur in a mobile network. Three machine learning techniques are presented in this study and compared with regard to accuracy. This study demonstrates that the appropriate machine learning technique improves the accuracy of the model. By using the decision tree as a machine learning model, it was possible to predict solutions to network failures, with an error rate less than 2%. In addition, the use of Machine Learning makes it possible to eliminate steps in the network failure processing chain;resulting in reduced service disruption time and improved the network availability which is a key network performance index.
