Application of Grey Prediction in a GA-BP Power Theft Algorithm

被引：0

作者：

Chen Xiaofeng ^{[1
]}

Xu Zhongping ^{[1
]}

Zhang Lipeng ^{[1
]}

Zhu Feng ^{[1
]}

Qi Xiaoming ^{[1
]}

Chen Fangzhen ^{[2
]}

机构：

[1] State Grid Informat & Telecommun Accenture Inform, Beijing 100032, Peoples R China

[2] Pingdingshan Power Supply Co State Grid Henan Ele, Pingdingshan 467000, Peoples R China

来源：

FUZZY SYSTEMS AND DATA MINING VI | 2020年 / 331卷

关键词：

Genetic Algorithm; Neural Network; Electricity Theft Prediction Model; Grey Model; Electricity Anti-Theft; NEURAL-NETWORK;

D O I：

10.3233/FAIA200692

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Statistics show that power theft is one of the main reasons for the dramatic increase in power grid line loss. In this paper, a genetic algorithm is used to optimize a neural network and establish a power theft prediction model. With the grey prediction model, the predicted values of variables are obtained and then applied to the prediction model of a GA-BP neural network to obtain relatively accurate predictions from limited samples, reducing the absolute error. Through the two levels of prediction and analysis, the model is demonstrated to have good universality in predicting power theft behavior, and is a practical and effective method for power companies to carry out power theft analysis.

引用

页码：125 / 134

页数：10

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