基于OLAP分析和关联规则的区域能耗预警系统研究

The research of regional energy consumption EWS based on OLAP analysis and association rules

为分析多维能耗数据,研究区域能耗数据内部隐含的各种异常相关性问题,在自主开发的能源监测系统上提出了利用基于数据仓库的OLAP分析和改进的分层挖掘Apriori算法,并以此建设成一套区域能耗预警系统,从而提高区域能耗监察管理和预警能力.在原系统上,通过建立一个区域能耗数据的输入输出模型作为研究对象,以企业申报数据为数据源建立数据仓库,作OLAP的多维数据分析,并在此基础上采用改进的Apriori算法挖掘预警的关联规则,最终发现隐含在内部的知识.系统以某市的实际数据为数据源进行验证,得出的数据分析更加直观、立体,预警知识也与实际情况相符合,值得在实践中应用.

In order to analyze the multi-dimensional energy consumption data and research kinds of exception - related issues hidden in the regional energy consumption data, a method is proposed based on the OLAP analysis in data warehouse and the improved layered mining Apriori algorithm on the developed system of energy monitoring is studied. The early warning system of regional energy consumption is developed and thereby the capabilities of regional energy management and early warning are enhanced. Basing on this original system, the IPO model of regional energy consumption is taken as the researched target, and the declaratory data from enterprise is taken as the data source in data warehouse in order to realize the multi-dimensional data analysis with OLAP platform. Based on these work, the improved Apriori algorithm is applied to mine the association rules for early warming in order to find the hidden knowledge in data source. The actual data source in a city is used to verify the method and the analysis results are more intuitive and comprehensive. The warning knowledge is consistent with the actual situation. It is worthy to be applied in practice.