Use of artificial networks to signify the onset of dynamic catastrophes in engineering systems is a simple and efficient strategy. Here an ordinal partition network and its construction from time series are introduced. The selection of mapping parameter is discussed in detail, which may significantly enhance the performance of the proposed method. Topological properties of the resulting network can sensitively detect the dynamic changes of original underlying systems, making the strategy workable. A Catastrophe Prediction Index (CPI) is proposed to serve as a monitoring indicator for pre-warning catastrophe events. The numerical results verify the feasibility of the proposed method.

中文翻译：

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序数分区网络多模块浮式平台的灾情预警

使用人工网络来表示工程系统中动态灾难的发生是一种简单而有效的策略。这里介绍一个序数划分网络及其从时间序列的构建。详细讨论了映射参数的选择，这可以显着提高所提出方法的性能。所得网络的拓扑特性可以灵敏地检测到原始底层系统的动态变化，使该策略可行。提出巨灾预测指数（CPI）作为预警巨灾事件的监测指标。数值结果验证了所提方法的可行性。