Open AccessResearch on the Cost Control Model of Power Gird Maintenance Based on Fuzzy Pattern Recognition Theory
Author(s) -
MA Xing-bin,
Suiyu Zhang,
Moxiao Li
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/453/1/012060
Subject(s) - fuzzy logic , range (aeronautics) , computer science , cluster analysis , data mining , eigenfunction , function (biology) , fuzzy clustering , process (computing) , cluster (spacecraft) , construct (python library) , reliability engineering , control (management) , power (physics) , operator (biology) , mathematical optimization , operations research , mathematics , artificial intelligence , engineering , eigenvalues and eigenvectors , biochemistry , physics , chemistry , repressor , quantum mechanics , evolutionary biology , transcription factor , gene , biology , programming language , aerospace engineering , operating system
The power grid lines and equipment maintenance of power enterprises is a complicated construction process, the cost of which is affected by meteorological and geographical factors, and the influence mode is uncertain. Using fuzzy clustering method and the threshold intervals of the objective function in clusters, this paper builds a predictive control model to control the project cost. This model uses relative fuzzy operator to build fuzzy matrix, construct correlation between factors, and describe the factors’ effect. Extracting the cluster’s eigenfunction, and defining the boundaries of various clusters, we determined the type of the predicted points and the range of the objective function. When the actual cost of the maintenance project is within the range calculated by the cost model, then it is normal. If the actual cost exceeds this range, then further analysis of all the aspects of the cost is needed to find out the reason.