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基于Apriori算法和卷积神经网络的配电设备运行效率主要影响因素挖掘

Method Based on Apriori Algorithm and Convolution Neural Network for Mining Main Influencing Factors of Distribution Equipment Operation Efficiency

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【作者】 白浩袁智勇孙睿张强史训涛

【Author】 BAI Hao;YUAN Zhiyong;SUN Rui;ZHANG Qiang;SHI Xuntao;Electric Power Research Institute,China Southern Power Grid Co.,Ltd.;Key Laboratory of the Ministry of Education on Smart Power Grids (Tianjin University);

【机构】 南方电网科学研究院智能电网教育部重点实验室(天津大学)

【摘要】 针对目前配电系统运行效率研究方面缺少评价手段且缺少内在原因的探究方法的问题,提出了一种基于Apriori算法和卷积神经网络的配电设备运行效率主要影响因素挖掘方法。首先,提出配电设备日运行效率的计算方法;其次,分析可能影响运行效率的原因,提出基于K-means聚类和Apriori算法的运行效率主要影响因素的挖掘方法;然后,基于卷积神经网络,提出运行效率与主要影响因素之间关系的定量度量方法;最后利用算例分析,验证了该文方法的可行性。

【Abstract】 In view of the lack of evaluation methods and research methods for internal causes in current research of distribution system operation efficiency,this paper proposes a method based on Apriori algorithm and convolution neural netw ork for mining the main influencial factors of distribution equipment operation efficiency. Firstly,according to the definition,the calculation method for daily operation efficiency of distribution equipment is proposed; Secondly,the reasons that may affect the operation efficiency are analyzed,and the method based on K-means clustering and Apriori algorithm for mining the main influencing factors of operation efficiency is proposed; Thirdly,the quantitative measurement method for the relationship betw een operation efficiency and main influencing factors is proposed on basis of convolution neural netw ork; Finally,by using programming,the feasibility of this method is verified.

【基金】 南方电网公司科技项目(ZBKJXM20180220)~~
  • 【文献出处】 电力建设 ,Electric Power Construction , 编辑部邮箱 ,2020年03期
  • 【分类号】TM73;TP183
  • 【被引频次】6
  • 【下载频次】287
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