Open AccessResearch on state prediction of secondary device in smart substation based on dynamic interval weighted fuzzy c-means algorithm
Author(s) -
Chen Zhongyang,
Peng-Fei Zhang,
Mahuan
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1486/3/032044
Subject(s) - cluster analysis , interval (graph theory) , convergence (economics) , computer science , state (computer science) , data mining , fuzzy clustering , stability (learning theory) , fuzzy logic , algorithm , artificial intelligence , mathematics , machine learning , combinatorics , economics , economic growth
A weighted fuzzy clustering algorithm based on dynamic interval is proposed to solve the problem of inaccuracy of missing attributes in clustering. By selecting the index that can reflect the secondary equipment state of intelligent substation comprehensively and combining with the weighted fuzzy clustering algorithm based on dynamic interval, the clustering classification result of the whole secondary equipment state of intelligent substation can be obtained accurately. According to the result, the corresponding maintenance strategy is adopted. The experimental results show that the weighted fuzzy clustering algorithm based on dynamic interval can effectively improve the clustering accuracy and the stability of the convergence, which can be very good to adapt themselves to the secondary device state overhaul.