Some Aspects of Combining Data and Models in Process Engineering,Chemie Ingenieur Technik

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Some Aspects of Combining Data and Models in Process Engineering
Chemie Ingenieur Technik ( IF 1.5 ) Pub Date : 2020-04-22 , DOI: 10.1002/cite.202000007
Raoul Heese ₁ , Julia Nies ₁ , Michael Bortz ₁

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Observing phenomena under defined conditions and building mathematical models to make further predictions are essential ingredients of natural and engineering sciences. Recent technological and methodical advances make large and high‐dimensional simulation data accessible to model building and therefore to optimization. In this article, selected machine learning methods are highlighted and applied to example data from simple flow sheet simulations. Furthermore, the essential outcomes of the workshop dealing with combination of data and models during the Tutzing Symposium 2019 are summarized.

中文翻译：

在流程工程中将数据和模型结合在一起的某些方面

在定义的条件下观察现象并建立数学模型以进行进一步的预测是自然科学和工程科学的基本要素。最新的技术和方法上的进步使大型高维仿真数据可用于模型构建，从而可进行优化。在本文中，突出显示了选定的机器学习方法，并将其应用于来自简单流程图模拟的示例数据。此外，总结了2019年Tutzing研讨会上有关数据和模型组合的研讨会的主要成果。

更新日期：2020-04-22

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