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Lstm-Based Anomaly Detection For Non-Linear Dynamical System, Yue Tan, Chungjing Hu, Kuan Zhang, Kan Zeng, Ethan A. Davis, Jae Sung Park

Department of Mechanical and Materials Engineering: Faculty Publications

Anomaly detection for non-linear dynamical system plays an important role in ensuring the system stability. However, it is usually complex and has to be solved by large-scale simulation which requires extensive computing resources. In this paper, we propose a novel anomaly detection scheme in non-linear dynamical system based on Long Short-Term Memory (LSTM) to capture complex temporal changes of the time sequence and make multi-step predictions. Specifically, we first present the framework of LSTM-based anomaly detection in non-linear dynamical system, including data preprocessing, multi-step prediction and anomaly detection. According to the prediction requirement, two types of training modes are explored …