Work

EvolGCN: A Co-Evolutionary Graph Convolutional Network Model for Dynamically Spatio-Temporal Anomaly Event Inference

Year: 2025

Type: article

Source: IEEE Transactions on Dependable and Secure Computing

DOI: 10.1109/tdsc.2025.3548671

Authors: Xiaoming Liu, Hang Pu, Zhuo Chen, Zhanwei Zhang, Yu Lan, Chao Shen

Institution: Xi'an Jiaotong University

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Fundamental Research Funds for the Central Universities

Awards: G1146122701, G1781846416, G2528846581, G2780744378, G5117753419, G5443852138, G6034313629, G7155321176, G8044788455, G8983850641

OpenAlex ID: W4408180997

FWCI: 0.831

Cites: 49

Cited by: 2

Related to: 10