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An Intelligent Earthquake Early Waring Model Using JRG Sub-cluster Statistics Theory

机译:基于JRG子类统计理论的智能地震预警模型

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Using strain precursor to predict the earthquake has proven to be crucial for earthquake early warning. However, there is currently problem that it is hard to establish more effective intelligent analyzing models for earthquake early warning. In this paper, we introduced the core concept and ideas of JRG Sub-cluster statistics theory and three risk limits at first. Meanwhile, we put forward the analyzing models for earthquake early warning system using JRG Sub-cluster theory. Then, the architecture of earthquake early warning system integrating early warning model, RS and GIS was put forward. Finally, Earthquake Early Warning System based on this architecture was implemented.
机译:事实证明,使用应变前兆来预测地震对于地震预警至关重要。但是,目前存在难以建立更有效的地震预警智能分析模型的问题。本文首先介绍了JRG子集群统计理论的核心概念和思想,首先介绍了三个风险极限。同时,利用JRG子聚类理论提出了地震预警系统的分析模型。然后,提出了结合预警模型,RS和GIS的地震预警系统架构。最后,实现了基于该架构的地震预警系统。

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