摘要
影响配电网设备提前退役的因素复杂多样,而且多种因素之间互相作用。为了筛选出影响设备提前退役的主要因素候选集,可以利用数据挖掘算法得到其中关联规则。其中,Apriori算法是最经典的挖掘关联规则的算法。但是传统的Apriori算法时间复杂度过大,计算效率不高。针对这一现状,提出一种基于三维矩阵的Apriori优化算法,通过建立三维矩阵以及简约数据库的方式,减少了传统算法中的计算冗余,挖掘出影响配电网设备提前退役的因素频繁项集。结果表明:改进算法能够得到配电网设备退役因素的关联规则并明显提高计算效率。
The factors affecting early decommissioning of distribution network equipment are complex and diverse,which are interacting with each other.In order to filter out the main candidate set of factors,data mining algorithms can be used to obtain association rules among them.Apriori algorithm is the most classical algorithm for mining association rules.However,the huge time complexity of the Apriori algorithm,the computational efficiency is too low.To address this problem,an improved Apriori algorithm based on three-dimensional matrix was proposed to reduce the computational redundancy in the Apriori algorithm by establishing a three-dimensional matrix and streamlining the database,and frequent item sets of factors affecting early decommissioning of distribution network equipment were mined.The results show the improved algorithm can get the association rules of the decommissioning factors of distribution network equipment and improve the calculation efficiency obviously.
作者
廖孟柯
樊冰
李忠政
付林
舒楠
LIAO Meng-ke;FAN Bing;LI Zhong-zheng;FU Lin;SHU Nan(Economic and Technical Research Institute,State Grid Xinjiang Electric Power Co.,Ltd., Urumqi 830002, China;School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)
出处
《科学技术与工程》
北大核心
2021年第24期10381-10386,共6页
Science Technology and Engineering
基金
国家自然科学基金(51677065)
国家电网有限公司科技项目(5400-202056131A-0-0-00)。
关键词
配电网设备
数据挖掘
APRIORI算法
设备退役
distribution network equipment
data mining
Apriori algorithm
equipment decommissioning
