Electricity stealing user identification system based on deep well network

The invention relates to the technical field of power detection, in particular to an electricity stealing user identification system based on a deep well network. The system comprises a power consumption behavior modeling module, a time sequence analysis module, a depth feature detection module, an abnormal mode recognition module, an incremental behavior updating module, a dynamic threshold self-adaption module, a regularization network optimization module and a geographic space risk analysis module. According to the invention, by applying the recurrent neural network or the long-short-term memory network, analyzing the power consumption behavior, generating the user power consumption behavior model and applying the time sequence analysis module, the capability of periodicity and trend information is improved, and the feature detection efficiency is improved through the combination of the auto-encoder and the convolutional neural network. The application of a support vector machine and K-means clustering pro