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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >Robustness of declarative modeling languages: Improvements via probability-one homotopy
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Robustness of declarative modeling languages: Improvements via probability-one homotopy

机译:声明式建模语言的鲁棒性:通过概率一同伦的改进

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摘要

Robustness issues with steady-state initialization remain a barrier in the practical use of declarative modeling languages for multi-domain modeling of large, complex, and heterogeneous technical systems. The objective of this paper is to illustrate how probability-one homotopy, an established method from topology, can solve this issue. This is achieved by establishing a framework for application-specific probability-one homotopy in declarative modeling languages. The analysis is based on domain-specific probability-one homotopy maps, which were reformulated in a declarative fashion. Additionally, a novel probability-one homotopy map and associated coercivity proof is introduced for a class of thermo-fluid dynamics problems. It was found that the approach enables robust initialization for declarative modeling languages on several test cases and leads to a concise declarative problem formulation.
机译:稳态初始化的稳健性问题仍然是在大型,复杂和异构技术系统的多域建模中使用声明性建模语言的实际障碍。本文的目的是说明概率一同态方法(一种通过拓扑建立的方法)如何解决此问题。这是通过在声明性建模语言中建立特定于应用程序的概率一同义的框架来实现的。该分析基于以声明方式重新制定的特定于域的概率一同型图。此外,针对一类热流体动力学问题,引入了一种新颖的概率一同伦映射和相关的矫顽力证明。结果发现,该方法可以在几个测试用例上对声明式建模语言进行可靠的初始化,并导致简洁的声明式问题表述。

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