Imbalanced-electricity-data-based Intelligent Monitoring System against Electricity Theft
The present study designed an anti-electricity-theft intelligent monitoring system based on imbalanced energy data.After the preprocessing of electricity load data,the system realizes rapid determination of users with abnormal behaviors by using the combined algorithm of random oversampling examples-gradient boosting decision tree to construct an intelligent mathematical model for monitoring anomalies of metering devices and electric consumption anomalies of users.Based on this,an embedded expert analysis system is developed to achieve online monitoring and analysis of electricity data,automatically display abnormal electric consumption data,and locate electricity thefts.
imbalanced datarandom oversampling examplesgradient boosting decision treeanti-theft system
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