Detection of Abnormal Electricity Consumption Behavior in the Aquaculture Industry Based on Feature Selection
With the development of smart grid and Internet of Things technology,abnormal electricity consumption behavior detection has become particularly important.This paper proposes an abnormal electricity consumption behavior detection method based on TOPSIS feature selection.By using electricity consumption data from users in the aquaculture industry to calculate the relative closeness between each feature and the ideal point and negative ideal point,the features are sorted and the most representative features are selected.The experimental results show that this method can effectively improve the performance of the anomaly de-tection model,with high accuracy and reliability,providing strong support for electricity safety management in the aquaculture industry.
TOPSISfeature selectionabnormal electricity usage behavior detectionbreeding industry
万方数据
维普
