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发明公开
CN104361433A 一种电网运行KPI数据模式自学习的方法和系统 无效 - 撤回

一种电网运行KPI数据模式自学习的方法和系统
摘要：
本发明涉及一种电网运行KPI数据模式自学习的方法和系统，该方法通过ETL技术按照需求对收集的电网运行数据进行数据抽取、数据转换和清洗得到电网运行KPI数据，并将清洗后的电网运行KPI数据装载到电网运行KPI数据仓库中，然后利用C4.5算法对装载到电网运行KPI数据仓库中的数据进行电网运行KPI数据挖掘，通过特征分析、关联分析和聚类决策分析得到KPI数据关联关系，再通过设置可信门槛过滤得到被接受的KPI数据关联关系，并在知识验证后得到新的电网运行KPI数据模式存储于电网运行KPI经验知识库中。该方法能够获取确信可使用的传统电网运行研究理论未发现的扩展知识，为丰富改善电网运行人员的专业知识和能力提供了基础，进而达到精细化管理。
摘要（英）：

The invention relates to a grid operation KPI (key performance indicator) data self-learning method and system. Through the ETL (extract, transform and load) technology, collected grid operation data is subjected as required to data extraction, data transformation and washing to obtain grid operation KPI data; the washed grid operation KPI data is loaded to a grid operation KPI data warehouse; the data loaded to the grid operation KPI data warehouse is subjected to grid operation KPI data mining through a C4.5 algorithm; a KPI data correlation relationship is obtained through feature analysis, correlation analysis and clustering decision analysis; an accepted KPI data correlation relationship is obtained through trusted threshold filtering; after knowledge verification, a new grid operation KPI data mode is obtained and stored in a grid operation KPI experience and knowledge base. According to the method, knowledge expansion surely available and undiscovered by the traditional grid operation research theories, basis for enriching and improving specialized knowledge and capacities of grid operation personnel is provided, and fine management is achieved accordingly.

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