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Automated parameter specification in dynamic feedback models based on behavior pattern features

机译:基于行为模式特征的动态反馈模型中的自动参数指定

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摘要

In various stages of a modeling study, the developer/user encounters the need for identification of specific values for certain model parameters. However, due to the non-linear nature of these models it is generally hard to foresee changes in the dynamic behavior as a consequence of even marginal parameter changes. Thus, the need for an automated and efficient search approach is very clear. A behavior pattern-based parameter search approach and results obtained from various test experiments are presented in this paper. The pattern identification algorithm used enables a parameter search process based on qualitative features of a desired behavior pattern, even in the absence of a reference data series. The approach conducts the search process so as to obtain values for the model parameters that yield an output that matches the desired behavior in terms of its qualitative pattern features. Experiments conducted reveal the viability of the approach as a support tool that can be used in model calibration, sensitivity analysis, validation, and policy design stages. Copyright © 2011 System Dynamics Society.
机译:在建模研究的各个阶段,开发人员/用户都需要识别某些模型参数的特定值。但是,由于这些模型的非线性性质,通常很难预见甚至边际参数变化会导致动态行为的变化。因此,非常需要自动高效的搜索方法。本文提出了一种基于行为模式的参数搜索方法以及从各种测试实验中获得的结果。即使在没有参考数据序列的情况下,所使用的模式识别算法也可以基于所需行为模式的定性特征进行参数搜索过程。该方法进行搜索过程,以获得模型参数的值,该模型参数的输出在定性模式特征方面与所需行为匹配。进行的实验表明,该方法作为支持工具的可行性,可用于模型校准,敏感性分析,验证和策略设计阶段。版权所有©2011系统动力学学会。

著录项

  • 来源
    《System dynamics review》 |2011年第2期|p.195-215|共21页
  • 作者

    Goeneng Yuecel; Yaman Barlas;

  • 作者单位

    Faculty of Technology Policy and Management, Delft University of Technology, Delft, The Netherlands;

    Industrial Engineering Department, Bogazici University, Istanbul, Turkey;

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  • 正文语种 eng
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