Infectious disease network key node identification method based on graph neural network
By using a graph neural network-based approach, combined with the SIR infectious disease model and graph attention mechanism, the identification of key nodes is optimized, solving the problem of identifying the influencing factors of nodes in infectious disease networks, and achieving accurate prediction of virus transmission and improved network stability.
CN116959745BActive Publication Date: 2026-07-24NANJING UNIV OF POSTS & TELECOMM
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING UNIV OF POSTS & TELECOMM
- Filing Date
- 2023-08-02
- Publication Date
- 2026-07-24
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Figure CN116959745B_ABST
Abstract
The application discloses a kind of infectious disease network key node identification method based on graph neural network, comprising the following steps: 1, by traditional SIR infectious disease model on the generated network simulates virus transmission process, constructs training data label;2, select the highest score of Kendall coefficient and the score obtained in step 1 is combined with feature, the selected network features are input into the attention model with multiple graph attention layers are introduced, in a variety of artificial networks are trained, to obtain the importance score ranking of each node more suitable;3, consider the "rich club" effect, the obtained ranking sequence is selected by the node selection algorithm based on distance 2-hop, select the node set that the influence range is further expanded.The application provides a new idea and tool for key node identification in complex network, and provides a scientific basis for network optimization and risk prevention.
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