论文标题
回顾性成本参数估计，并应用于空间天气建模
Retrospective Cost Parameter Estimation with Application to Space Weather Modeling
论文作者
论文摘要
本章回顾了标准参数估计技术，并介绍了DDDAS框架中新型的梯度 - 集合，无伴随的无数据驱动参数估计技术。该技术称为回顾性成本参数估计（RCPE），是由以高维非线性动力学，非线性参数化和表示模型为特征的大规模复杂估计模型的动机。通过在三个示例中估算未知参数来说明RCPE。在第一个示例中，通过考虑低阶非线性系统中的参数估计问题来研究RCPE的显着特征。在第二个示例中，使用标量测量值来估计对流系数和广义汉堡方程中的粘度。在最后的示例中，RCPE用于估计将时间温度变化与大气中温度的垂直梯度相关的热导率系数。
This chapter reviews standard parameter-estimation techniques and presents a novel gradient-, ensemble-, adjoint-free data-driven parameter estimation technique in the DDDAS framework. This technique, called retrospective cost parameter estimation (RCPE), is motivated by large-scale complex estimation models characterized by high-dimensional nonlinear dynamics, nonlinear parameterizations, and representational models. RCPE is illustrated by estimating unknown parameters in three examples. In the first example, salient features of RCPE are investigated by considering parameter estimation problem in a low-order nonlinear system. In the second example, RCPE is used to estimate the convective coefficient and the viscosity in the generalized Burgers equation by using a scalar measurement. In the final example, RCPE is used to estimate thermal conductivity coefficients that relate temporal temperature variation with the vertical gradient of the temperature in the atmosphere.
