Open AccessState Evaluation for Intelligent Distribution Terminal Units Based on Mining Association Rules
Author(s) -
Ling Zhu,
Yanning Ge,
Xiyu Song,
Zhao Wen,
Jianhua Guo
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/752/1/012015
Subject(s) - association rule learning , data mining , lift (data mining) , computer science , terminal (telecommunication) , fuzzy logic , artificial intelligence , computer network
The construction of Ubiquitous Power Internet of Things expands the content and scale of data in distribution network. In order to meet the demand of intelligent operation and maintenance of distribution terminals, this paper proposes a method of mining association rules in data to realize evaluation of distribution terminal units. In this method, firstly, the Apriori algorithm with directional constraint of terminals’ functional module is used to mine the correlation indicators system under each divided functional module of terminals. Secondly, the comprehensive measurement of confidence and lift degree is used to increase the objectivity of evaluation’s weights of indicators which found by mining associations rules. Then, combined with the fuzzy comprehensive evaluation method, according to the correlation indicators system, the status evaluation of intelligent distribution terminals is realized. Finally, the historical status data of the actual disabled terminals are selected to verify the good effectiveness of the method that described in this paper.