Dynamical System Multivariate Time Series

The Dynamical System Multivariate Time Series (DSMTS) Dataset consists of commands, external stimuli, and telemetry readings of a simulated complex dynamical system under fully nominal conditions (no outliers or anomalies). The DSMTS Dataset exhibits a set of desirable properties that make it very suitable for benchmarking Multivariate Time Series Forecasting especially for industrial processes of complex systems: Multivariate (17 variables) including sensors reading and control signals. It simulates the operational behaviour of an arbitrary complex system including: 4 Deliberate Actuations / Control Commands sent by a simulated operator / controller, for instance, commands of an operator to turn ON/OFF some equipment. 3 Environmental Stimuli / External Forces acting on the system and affecting its behaviour, for instance, the wind affecting the orientation of a large ground antenna. 10 Telemetry Readings representing the observable states of the complex system by means of sensors, for instance, a position, a temperature, a pressure, a voltage, current, humidity, velocity, acceleration, etc. 5 million timestamps. Sensors readings are at 1Hz sampling frequency. Pure signal ideal for robustness-to-noise analysis. The simulated signals are provided without noise: while this may seem unrealistic at first, it is an advantage since users of the dataset can decide to add on top of the provided series any type of noise and choose an amplitude. This makes it well suited to test how sensitive and robust detection algorithms are against various levels of noise. No missing data. You can drop whatever data you want to assess the impact of missing values on your detector with respect to a clean baseline.动力学系统多变量时间序列数据集（Dynamical System Multivariate Time Series Dataset, DSMTS）包含了完全标称工况下（无异常值或离群点）的模拟复杂动力学系统的控制指令、外部激励与遥测读数。 DSMTS数据集具备一系列优良特性，使其非常适用于多变量时间序列预测的基准测试，尤其适配复杂系统的工业流程场景： 该数据集为多变量形式（共17个变量），涵盖传感器读数与控制信号，可模拟任意复杂系统的运行行为，具体包含以下三类内容： 4项预设执行动作/控制指令：由模拟操作员或控制器发出，例如操作员对部分设备执行启停操作的指令； 3项环境激励/外部作用力：作用于系统并影响其运行状态，例如影响大型地面天线指向的风力； 10项遥测读数：通过传感器获取的复杂系统可观测状态数据，例如位置、温度、压力、电压、电流、湿度、速度、加速度等。 该数据集共包含500万个时间戳，传感器读数的采样频率为1Hz。 该数据集为纯净无噪信号，非常适用于抗噪声鲁棒性分析。尽管乍看之下模拟信号无噪声似乎不符合实际应用场景，但这一设计实则具备显著优势：数据集使用者可自行决定为原始序列添加任意类型的噪声，并自定义噪声幅值。这使得该数据集非常适合用于测试检测算法对不同强度噪声的敏感性与鲁棒性。 该数据集无缺失值，使用者可根据需求自行剔除部分数据，以基于干净的基准基线评估缺失值对检测算法的影响。