Open access
Date
2024-03-19Type
- Journal Article
Abstract
Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling techniques. While both approaches have complementary advantages there are often multiple ways to combine them into a hybrid model, and the appropriate solution will depend on the problem at hand. In this paper, we provide four base patterns that can serve as blueprints for combining data-driven components with domain knowledge into a hybrid approach. In addition, we also present two composition patterns that govern the combination of the base patterns into more complex hybrid models. Each design pattern is illustrated by typical use cases from application areas such as climate modeling, engineering, and physics. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000666244Publication status
publishedExternal links
Journal / series
Journal of Mathematics in IndustryVolume
Pages / Article No.
Publisher
SpringerSubject
Hybrid modeling; Physics-inspired AI; Design patternsOrganisational unit
00002 - ETH Zürich
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