Open Access
ARTICLE
Traffic Anomaly Detection Method Based on Improved GRU and EFMS-Kmeans Clustering
1 Science and Technology on Communication Networks Laboratory, The 54th Research Institute of CETC, Shijiazhuang, China
2 Department of Military Representative Office of General Military Equipment Development Shijiazhuang, Shijiazhuang, China
3 State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
* Corresponding Author: Yang Yang. Email: