Research And Implementation Of Base Station Inspection Decision System Based On Data Mining

The rapid development of the communications industry is inseparable from the normal operation of base stations. The base stations need security inspection and equipment troubleshooting in order to ensure them working stability and reliability. Massive amounts of inspection and troubleshooting data is scattered storage, so they can’t be unified analysis and storage. With the advocating of office automation and big data analytics, the traditional base stations’inspection is inefficient and backward. Development of computer technology and data mining techniques would be promote the development of stations’inspection more automated and intelligent.Base on the comprehensive operation support and intelligent management system of ANM Laboratory. With in-depth research and analysis of the inspection demand, data mining and key technologies, this paper elaborates the inspection of base stations analysis and decision system. And use SSH framework, Android platform and data mining technology to achieve the system. SSH achieves a low coupling and high scalability while the Android client provides an excellent user experience for data collection. Data mining achieve the function of analysis and decision. The system uses clustering analyzing the inspection data to discover frequent security risks. Meanwhile the system uses the classification algorithm analyzing the troubleshooting data to count high failure rate stations. The statistics would be the focus of next inspection. So the inspection work is no longer a mechanical repetition, it is more focused and purposeful detection. The system achieves a more scientific and intelligent inspection work.