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, discovering and visualizing connections and correlations in complex phenomena. The extracted knowledge is then validated with domain expertise, revealing potential and limitations of this method.

Produktinformationen

Titel:

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

Autor:

Massimiliano Botticelli

EAN:

9783731512950

ISBN:

3731512955

Format:

Kartonierter Einband

Herausgeber:

Karlsruher Institut für Technologie

Veröffentlichung:

03.07.2023

Anzahl Seiten:

210

Gewicht:

312g

Größe:

H210mm x B148mm x T14mm

Jahr:

2023

Untertitel:

Englisch

Weitere Produkte aus der Reihe "Reihe Informationsmanagement im Engineering Karlsruhe / Hrsg.: Karlsru"

Kartonierter Einband 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 von Massimiliano Botticelli

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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
Massimiliano Botticelli

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