Physics-Informed Regression: Parameter Estimation in Parameter-Linear Nonlinear Dynamic Models
物理信息回归:参数线性非线性动力模型的参数估计
We present a new efficient hybrid parameter estimation method based on the idea, that if nonlinear dynamic models are stated in terms of a system of equations that is linear in terms of the parameters, then regularized ordinary least squares can be used to estimate these parameters from time series data. We introduce the term "Physics-Informed Regression" (PIR) to describe the proposed data-driven hybrid technique as a way to bridge theory and data by use of ordinary least…