基于Apriori算法的电力系统二次设备缺陷数据挖掘与分析研究
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摘要
为了能够使电力系统二次设备运行维护及管理控制水平得到提高,基于电力系统二次设备缺陷数据提出了基于Apriori算法的电力系统二次设备缺陷数据挖掘及分析方法。首先,对关联规则和Apriori算法的思路进行了全面的分析,之后创建以关联规则为基础的电力系统二次设备缺陷模型,通过模型思考二次设备缺陷的主要属性,包括二次设备类型、生产厂家及缺陷原因、部位等。最后,将自动化设备缺陷数据作为例子,分析基于Apriori算法的电力系统二次设备缺陷数据挖掘及分析方法。通过分析结果表示,所提出的方法能够满足二次设备缺陷数据挖掘及分析需求,并且寻找导致数据缺陷的原因,还能够对设备家族性缺陷进行分析。
In order to improve the operation and maintenance of the two equipment of the power system and improve the management and control level,the method of data mining and analysis of two equipment defects of power system based on the Apriori algorithm is proposed based on the two equipment defect data. First,a comprehensive analysis of the association rules and the thinking of the Apriori algorithm is carried out. After that,the two equipment defect model of power system based on the association rules is created,and the main attributes of the two equipment defects,including the two equipment type,the manufacturer and the defect cause and the location,are thought through the model. Finally,taking the defect data of automation equipment as an example,we analyze the two equipment defect data mining and analysis method based on Apriori algorithm. The analysis results show that the proposed method can meet the data mining and analysis requirements of two equipment defects,and find the causes of data defects,and can also analyze the family defects of the equipment.
In order to improve the operation and maintenance of the two equipment of the power system and improve the management and control level,the method of data mining and analysis of two equipment defects of power system based on the Apriori algorithm is proposed based on the two equipment defect data. First,a comprehensive analysis of the association rules and the thinking of the Apriori algorithm is carried out. After that,the two equipment defect model of power system based on the association rules is created,and the main attributes of the two equipment defects,including the two equipment type,the manufacturer and the defect cause and the location,are thought through the model. Finally,taking the defect data of automation equipment as an example,we analyze the two equipment defect data mining and analysis method based on Apriori algorithm. The analysis results show that the proposed method can meet the data mining and analysis requirements of two equipment defects,and find the causes of data defects,and can also analyze the family defects of the equipment.
引文
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[3]张延旭,胡春潮,黄曙,等.基于Apriori算法的二次设备缺陷数据挖掘与分析方法[J].电力系统自动化,2017,41(19):147-151.
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[5]贾克斌,李含婧,袁野.基于Apriori算法的数据挖掘在移动医疗系统中的应用[J].北京工业大学学报,2017,43(3):394-401.
[6]张晓宁,李娜,朱方娥.利用Apriori算法进行船舶缺陷数据研究分析[J].舰船科学技术,2016,21(14):139-141.
[7]张继荣,王向阳.基于X ML数据挖掘的Apriori算法的研究与改进[J].计算机测量与控制,2016,24(6):178-180.
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[9]郭和攀,李其仲,黄妙华.基于Apriori算法的轿车参数配置数据挖掘[J].武汉理工大学学报,2016,19(12):15-16.
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[11]黄钧晟.云计算环境下基于Apriori算法的气象数据关联规则分析研究[D].南京:南京信息工程大学,2015.
[12]李晋芳.基于Apriori算法的数据挖掘算法研究[J].晋城职业技术学院学报,2014,7(2):60-62.
[13]程宪宝,胡必波,钱海军.基于Apriori算法的CCT成绩数据挖掘研究[J].齐齐哈尔大学学报:自然科学版,201,21(5):7-11.
[14]姜凯强,冯霄月.在数据挖掘中一种基于Mapreduce模型的Apriori算法研究[J].计算机光盘软件与应用,2014(1914):296-297.
[15]张小军,张浩,申丹丹.基于数据挖掘关联规则Apriori算法的优化对策分析[J].计算机光盘软件与应用,2014,18(7):308-309.
[2]姜美灵,邬惠国,肖英杰,等.基于Apriori算法的PSC检查船舶缺陷数据挖掘[J].水运管理,2014,36(4):7-9.
[3]张延旭,胡春潮,黄曙,等.基于Apriori算法的二次设备缺陷数据挖掘与分析方法[J].电力系统自动化,2017,41(19):147-151.
[4]丁丽.基于Apriori算法的用户行为数据挖掘研究[J].科技通报,2013,12(12):214-217.
[5]贾克斌,李含婧,袁野.基于Apriori算法的数据挖掘在移动医疗系统中的应用[J].北京工业大学学报,2017,43(3):394-401.
[6]张晓宁,李娜,朱方娥.利用Apriori算法进行船舶缺陷数据研究分析[J].舰船科学技术,2016,21(14):139-141.
[7]张继荣,王向阳.基于X ML数据挖掘的Apriori算法的研究与改进[J].计算机测量与控制,2016,24(6):178-180.
[8]周芳.基于关联规则Apriori算法的物联网海量数据挖掘系统研究[J].河北北方学院学报:自然科学版,2015,15(1):15-18.
[9]郭和攀,李其仲,黄妙华.基于Apriori算法的轿车参数配置数据挖掘[J].武汉理工大学学报,2016,19(12):15-16.
[10]玄文启.一种大数据挖掘技术——Apriori算法分析[J].中国科技信息,2015,21(22):39.
[11]黄钧晟.云计算环境下基于Apriori算法的气象数据关联规则分析研究[D].南京:南京信息工程大学,2015.
[12]李晋芳.基于Apriori算法的数据挖掘算法研究[J].晋城职业技术学院学报,2014,7(2):60-62.
[13]程宪宝,胡必波,钱海军.基于Apriori算法的CCT成绩数据挖掘研究[J].齐齐哈尔大学学报:自然科学版,201,21(5):7-11.
[14]姜凯强,冯霄月.在数据挖掘中一种基于Mapreduce模型的Apriori算法研究[J].计算机光盘软件与应用,2014(1914):296-297.
[15]张小军,张浩,申丹丹.基于数据挖掘关联规则Apriori算法的优化对策分析[J].计算机光盘软件与应用,2014,18(7):308-309.