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2024 | OriginalPaper | Chapter

6. Entwurfsfindung und Performanceoptimierung mit Machine Learning Methoden

Authors : Christoph Emunds, Clara-Larissa Lorenz, Jérôme Frisch, Christoph van Treeck

Published in: Künstliche Intelligenz im Bauwesen

Publisher: Springer Fachmedien Wiesbaden

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Zusammenfassung

Dieses Kapitel gibt eine Einführung in den Bereich des maschinellen Lernens zum Zwecke der Unterstützung von Gebäudesimulationen und der Optimierung von Gebäudeentwürfen aus Sicht eines Anwenders von Gebäudesimulationssoftware. Der folgende Abschnitt motiviert die Entscheidung zur Entwurfsoptimierung in frühen Planungsphasen und diskutiert die Hindernisse für umfangreiche Entwurfsexplorationen bei der Verwendung von physikalischen Gebäudesimulationen. Anschließend wird ein Überblick über die Anwendung von Machine Learning Methoden zur Unterstützung von physikalischen Simulationen in zwei Anwendungsbereichen gegeben. Im weiteren Verlauf des Kapitels wird die Vorgehensweise bei der Implementierung und Nutzung solcher Machine Learning Methoden näher erläutert. Der letzte Abschnitt bietet eine Zusammenfassung des Kapitels und einen Ausblick über potenzielle zukünftige Anwendungen.

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Title: Entwurfsfindung und Performanceoptimierung mit Machine Learning Methoden
Authors: Christoph Emunds
Clara-Larissa Lorenz
Jérôme Frisch
Christoph van Treeck
Publisher: Springer Fachmedien Wiesbaden
Book: Künstliche Intelligenz im Bauwesen
Print ISBN: 978-3-658-42795-5

Electronic ISBN: 978-3-658-42796-2

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-658-42796-2_6

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Zusammenfassung

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