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Anomaly Detection for Complex Physical System via Nonlinear Relationship Modeling

机译:基于非线性关系建模的复杂物理系统异常检测

摘要

Methods and systems for detecting anomalies include determining a predictive model for each pair of a set of time series, each time series being associated with a component of a system. New values of each pair of time series are compared to values predicted by the respective predictive model to determine if the respective predictive model is broken. A number of broken predictive models is determined. An anomaly alert is generated if the number of broken predictive models exceeds a threshold.
机译:用于检测异常的方法和系统包括为一组时间序列的每一对确定预测模型,每个时间序列与系统的组件相关联。将每个时间序列对的新值与相应的预测模型预测的值进行比较,以确定相应的预测模型是否被破坏。确定了许多破损的预测模型。如果损坏的预测模型的数量超过阈值,则会生成异常警报。

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