Title: An Analytical Method of Data Mining on Voltage Sag based on Gray Target Theory and Cloud Model
Abstract: Summarizing the knowledge contained in voltage sag event records, to mine the relationship between different fault scenarios and site voltage sag severity, which can provide valuable information for management departments to make decisions. In this paper, the adaptive Gaussian cloud transformation algorithm is used to discretize the continuous data related to voltage sag. Constructing the dimension matrix by scanning the original database transaction once, to replace the item sets in the traditional AprioriTid algorithm. Proposing an improved algorithm that has improved both space and time efficiency. Then, combined with the gray target theory, we build the index sequences based on membership, to construct the matching model between the actual scene and the strong association rules. Finally selecting the knowledge that can best reflect the law of the effect of voltage sag on site in the current scene in actual analysis. Practical example analysis shows the practicability and effectiveness of the proposed method.
Publication Year: 2018
Publication Date: 2018-09-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 2
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