论文标题
时间序列的参数杂交自动机的合成
Synthesis of Parametric Hybrid Automata from Time Series
论文作者
论文摘要
我们提出了一种从时间序列数据中合成线性混合自动机的算法方法。与现有方法不同，我们的方法提供了整个模型家族。从下面的意义上讲，家族中的每个模型都可以保证将输入数据捕获到精确误差ε时：对于每个时间序列，该模型都包含一个执行ε关闭到数据点。我们的构造允许从该家族中有效地选择一个模型，而精度误差ε最小。我们证明了该算法的效率及其在两个案例研究中找到精确模型的能力。
We propose an algorithmic approach for synthesizing linear hybrid automata from time-series data. Unlike existing approaches, our approach provides a whole family of models. Each model in the family is guaranteed to capture the input data up to a precision error ε, in the following sense: For each time series, the model contains an execution that is ε-close to the data points. Our construction allows to effectively choose a model from this family with minimal precision error ε. We demonstrate the algorithm's efficiency and its ability to find precise models in two case studies.
