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Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes

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In this work, a novel knowledge discovery framework able to analyze data produced in the Gasoline Direct Injection (GDI) context through machine learning is presented and validated. This approach is able to explore and exploit the investigated design spaces based on a limited number of observations,...

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Auteur principal: Botticelli, Massimiliano (auth)
Format: Électronique Chapitre de livre
Langue:anglais
Publié: KIT Scientific Publishing 2023
Collection:Reihe Informationsmanagement im Engineering Karlsruhe 2
Sujets:
Mechanical engineering & materials
Gasoline Direct Injection; Data-Driven Development; Machine Learning Application; Datengetriebene Entwicklung; Anwendung des Maschinellen Lernens; Knowledge Discovery; Benzin-Direkteinspritzung
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