Tunnel network anomaly detection method based on domain adaptive depth auto-encoder

The invention relates to a tunnel network anomaly detection method based on a domain adaptive depth auto-encoder, and belongs to the technical field of tunnel network anomaly detection. The method comprises the steps of data acquisition and preprocessing, training and updating of an anomaly detection source domain model, dynamic threshold calculation of anomaly detection, detection of abnormal data and the like. According to the method, operations such as preprocessing and anomaly detection can be directly performed on the tunnel network on the edge side, the processing speed of a monitoring system is improved, and the processing time delay is effectively shortened. Meanwhile, based on the normal reference value of the current network state, the abnormal threshold range is reasonably set, and the situations of abnormal information missing report, false report and the like caused by fixed setting of the threshold are avoided. 本发明涉及一种基于域自适应深度自编码器的隧道网络异常检测方法，属于隧道网络异常检测技术领域。该方法包括数据采集及预处理、异常检测源域模型的训练及更新、异常检测的动态阈值计