基于决策树算法的电网调度频繁数据挖掘系统设计

Design of frequent data mining system for power grid dispatching based on decision tree algorithm

针对现有电网调度运行日志与智能操作票系统功能难以满足调度任务需要的问题,亟需对系统进行技术升级与结构改造。文中设计了一种基于决策树算法的电网调度频繁数据挖掘系统,利用C4.5决策树分类算法的训练自学习特性,结合电网频繁调度数据,建立数据挖掘模型。在模型基础上构建历史调度操作指令与典型调度操作指令智能学习知识库,并设计了相应的防误功能,从而得到电网调度频繁数据挖掘系统。文中所设计的电网调度频繁数据挖掘系统能够有效实现对电网调度频繁数据的分析与挖掘,具有较快的响应速度与防误性能,可以有效提升电网调度的可靠性。

In view of the problem that the functions of the existing dispatching operation log and intelligent operation ticket system are difficult to meet the needs of dispatching tasks,it is urgent to upgrade the technology and structure of the system.In this paper,a frequent data mining system of power grid dispatching based on decision tree algorithm is designed.By using the training self-learning characteristics of C4.5 decision tree classification algorithm and combined with frequent dispatching data of power grid,a data mining model is established.On the basis of the model,the intelligent learning knowledge base of historical dispatching operation instructions and typical dispatching operation instructions is constructed,and the corresponding error prevention function is designed,so as to obtain Frequent data mining system for power grid dispatching.The frequent data mining system designed in this paper can effectively analyze and mine the frequent data of power grid dispatching,with fast response speed and error prevention performance,and can effectively improve the reliability of power grid dispatching.