High-accuracy Detection Algorithm of Electricity Theft Behavior Based on Multi-objective Optimization Time-domain Convolutional Neural Network
With the diversity of current users'electricity consumption behaviors and the increasing concealing of electric theft behaviors,the detection rate of electric theft detection is high,and the false detection rate is also increasing,which makes it difficult for existing algorithms to meet the actual engineering requirements of high-accuracy electric theft inspection.In this paper,a high-accuracy electric theft detection algorithm based on multi-objective optimization of time-domain convolutional neural network is proposed.Firstly,the depth model is constructed based on the time-domain convolutional neural network,and the side output fusion structure is introduced to extract the high-low dimensional features of the user's electricity consumption information,and the feature fusion is carried out by the attention mechanism to improve the model's detection accuracy.Then model parameters are trained in two stages.In the first stage,the weight and threshold of the model are optimized based on the traditional gradient descent algorithm;in the second stage,objective functions of accuracy,detection rate and false detection rate are established based on the confusion matrix of power theft detection.The third-generation Non-dominated Sorting Genetic Algorithm(NSGA-Ⅲ)was used to optimize the model training,improve the detection rate of electric theft and reduce the false detection rate,and based on this,a high-accuracy detection algorithm for electric theft behavior of multi-objective optimization time-domain convolutional neural network was established.The experimental platform of electric theft detection is developed to verify the proposed algorithm.Finally,through the actual data of the power grid and the experimental platform verification,the results show that the proposed algorithm can reduce the false detection rate and increase the detection rate by 10％,which is more in line with the actual demand of highly accurate detection of electricity theft in current engineering applications.
万方数据
维普
