TIME SERIES ANOMALY DETECTION METHOD AND APPARATUS, AND COMPUTER DEVICE AND STORAGE MEDIUM

摘要

A time series anomaly detection method and apparatus, and a computer device and a storage medium. The method comprises: using a first convolutional neural network to perform convolution processing on a time series data sample, so as to obtain a time series feature associated with a local neighboring time step (S101); using an attention mechanism to be associated with a global time step of the time series feature, so as to obtain a time series feature associated with the global time step (S102); using a variational auto-encoding algorithm to encode and decode the time series feature associated with the global time step, so as to obtain a reconstructed time series feature (S103); using a second convolutional neural network to perform convolution processing on the reconstructed time series feature, so as to obtain time series restoration data (S104); using the difference between the time series data sample and the time series restoration data to detect an outlier of the time series data sample, and completing the construction of a time series anomaly detection model (S105); and using the time series anomaly detection model to perform detection on time series data to be subjected to detection, so as to obtain an outlier of said time series data (S106). The applicability and accuracy of a model are thus improved.