Attention-based spatial–temporal multi-graph convolutional networks for casualty prediction of terrorist attacks

Zhiwen Hou; Yuchen Zhou; Xiaowei Wu; Fanliang Bu

doi:10.1007/s40747-023-01037-z

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JOURNAL ARTICLE

Attention-based spatial–temporal multi-graph convolutional networks for casualty prediction of terrorist attacks

Zhiwen Hou Yuchen Zhou Xiaowei Wu Fanliang Bu

Year: 2023 Journal: Complex & Intelligent Systems Vol: 9 (6)Pages: 6307-6328 Publisher: Springer Science+Business Media

DOI: 10.1007/s40747-023-01037-z

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Keywords:

Computer science Terrorism Adjacency list Graph Convolution (computer science) Time series Spatial analysis Data mining Artificial intelligence Theoretical computer science Machine learning Geography Algorithm Mathematics Artificial neural network Statistics

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Topics

Terrorism, Counterterrorism, and Political Violence

Social Sciences → Social Sciences → Sociology and Political Science

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Data-Driven Disease Surveillance

Health Sciences → Medicine → Epidemiology

Attention-based spatial–temporal multi-graph convolutional networks for casualty prediction of terrorist attacks

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