Mobius建模环境下的实验设计

T. Courtney, Shravan Gaonkar, M. McQuinn, Eric Rozier, W. Sanders, P. Webster
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引用次数: 6

摘要

复杂系统的模型通常包含重要速率、概率和初始状态值的模型参数。通过改变参数值,系统建模者可以在广泛的系统和环境假设下研究系统的行为。然而,对大型模型的参数空间进行详尽的探索在计算上是昂贵的。实验技术的设计提供了输出变量对各种输入参数的敏感程度的信息。实验设计使得通过运行比不太严格的技术所需的更少的实验来找到优化系统测量输出的参数值成为可能。本文描述了集成在Mobius工具中的实验技术的设计。
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Design of Experiments within the Mobius Modeling Environment
Models of complex systems often contain model parameters for important rates, probabilities, and initial state values. By varying the parameter values, the system modeler can study the behavior of the system under a wide range of system and environmental assumptions. However, exhaustive exploration of the parameter space of a large model is computationally expensive. Design of experiments techniques provide information about the degree of sensitivity of output variables to various input parameters. Design of experiments makes it possible to find parameter values that optimize measured outputs of the system by running fewer experiments than required by less rigorous techniques. This paper describes the design of experiments techniques that have been integrated in the Mobius tool.
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