停电范围内配网设备信息智能挖掘系统设计

Design of intelligent information mining system for distribution network equipment in power outage range

针对人工方法受到配网动态环境影响,导致信息筛选查全率低和挖掘误差大的问题,提出了停电范围内配网设备信息智能挖掘系统设计。动态分析和实时分析停电情况,设计系统硬件结构,由此构建空间数据引擎,为存储系统所需的关系表或XML文档创建数据库,以优化数据库性能。应用Apriori计算方法对停电范围内配网设备中信息传输通道分类,从而更好识别和分类信息,通过Map/Reduce并行编程模型,将大规模计算任务扩展到无限规模机器集群上完成数据归一,由此完成挖掘系统设计。通过实验可知,该系统最高查全率为93%,最高信息挖掘误差为0.15,为信息智能挖掘提供精准挖掘技术。

In view of the low recall rate of information screening and large mining error caused by the influence of the dynamic environment of distribution network,the design of intelligent information mining system for distribution network equipment within the scope of power failure is proposed.Dynamic analysis and real-time analysis of power failure,design the hardware structure of the system,thus building a spatial data engine,creating a database for the relational tables or XML documents needed by the storage system,so as to optimize the database performance.The Apriori computing method is applied to classify the information transmission channels in the distribution network equipment within the scope of power failure,so as to better identify and classify the information.Through the Map/Reduce parallel programming model,the large-scale computing task is extended to the infinite scale machine cluster to complete the data normalization,thus completing the excavation system design.The experiment shows that the highest recall rate of the system is 93%,and the maximum information mining error is 0.15,which provides accurate mining technology for information intelligent mining.