Method and System for Model Validation for Dynamic Systems Using Bayesian Principal Component Analysis
    2.
    发明申请
    Method and System for Model Validation for Dynamic Systems Using Bayesian Principal Component Analysis 审中-公开
    使用贝叶斯主成分分析的动态系统模型验证方法与系统

    公开(公告)号:US20120209575A1

    公开(公告)日:2012-08-16

    申请号:US13025497

    申请日:2011-02-11

    IPC分类号: G06F17/10

    摘要: A method and system for assessing the accuracy and validity of a computer model constructed to simulate a multivariate complex dynamic system. The method and system exploit a probabilistic principal component analysis method along with Bayesian statistics, thereby taking into account the uncertainty and the multivariate correlation in multiple response quantities. It enables a system analyst to objectively quantify the confidence of computer models/simulations, thus providing rational, objective decision-making support for model assessment. The validation methodology has broad applications for models of any type of dynamic system. In a disclosed example, it is used in a vehicle safety application.

    摘要翻译: 一种用于评估构建为模拟多变量复杂动态系统的计算机模型的准确性和有效性的方法和系统。 该方法和系统利用贝叶斯统计学的概率主成分分析方法,从而考虑到多个响应量的不确定性和多变量相关性。 它使系统分析师能够客观地量化计算机模型/模拟的置信度,从而为模型评估提供合理,客观的决策支持。 验证方法对于任何类型的动态系统的模型都有广泛的应用。 在公开的示例中,其用于车辆安全应用中。