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Prediction of geological earthquake disaster event evolution results based on KGCN
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Shuyu SHAO1, 2, Yang ZHANG1, 2, Yan LIU1, 2
China Safety Science Journal | 2025, 35(2) : 212 - 219
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China Safety Science Journal | 2025, 35(2): 212-219
• Public safety •
Prediction of geological earthquake disaster event evolution results based on KGCN
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Shuyu SHAO1, 2, Yang ZHANG1, 2, Yan LIU1, 2
Affiliations
  • 1 School of logistics，Beijing Wuzi University，Beijing 101149，China
  • 2 Beijing Logistics System and Technology Key Laboratory，Beijing 101149，China
Published: 2025-02-28 doi: 10.16265/j.cnki.issn1003-3033.2025.02.0516
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To enhance the accuracy and reliability of geological earthquake disaster events predictions，a predictive model combining knowledge graph with GCN was proposed. Initially，the knowledge graph for geological earthquake disaster events was constructed，and the multi-source disaster-related information was consolidated into structured data. Then，the KGCN model was employed for deep learning of entities and relationships within the knowledge graph，uncovering potential association rules to forecast the evolution of disasters. Finally，the effectiveness of the model was validated through a set of geological earthquake disaster cases. The results show that the predictive model combing knowledge graphs with GCN exhibits excellent effectiveness in forecasting the evolution of geological earthquake disaster events，especially in dealing with complex multi-source data. The information can be efficiently integrated，and potential relationships can be accurately uncovered by the model. Excellent prediction accuracy is achieved in various aspects，including disaster levels，casualty levels，and disaster victim categories. Notably，the accuracy in predicting the disaster emergency response levels reaches 89.92%.

knowledge graph convolutional network(KGCN)  /  geological earthquake disaster  /  disaster event  /  evolutionary result  /  knowledge graph  /  graph convolution neural network(GCN)
Shuyu SHAO, Yang ZHANG, Yan LIU. Prediction of geological earthquake disaster event evolution results based on KGCN[J]. China Safety Science Journal, 2025 , 35 (2) : 212 -219 . DOI: 10.16265/j.cnki.issn1003-3033.2025.02.0516
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Year 2025 volume 35 Issue 2
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.02.0516
  • Receive Date：2024-09-12
  • Online Date：2025-07-05
  • Published：2025-02-28
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  • Received：2024-09-12
  • Revised：2024-11-14
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Affiliations
    1 School of logistics，Beijing Wuzi University，Beijing 101149，China
    2 Beijing Logistics System and Technology Key Laboratory，Beijing 101149，China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
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Genus		 种数
Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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