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.
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Taschenbuch. Zustand: Neu. 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 | Taschenbuch | Englisch | 2023 | Karlsruher Institut für Technologie | EAN 9783731512950 | Verantwortliche Person für die EU: KIT Scientific Publishing, Straße am Forum 2, 76131 Karlsruhe, info[at]ksp[dot]kit[dot]edu | Anbieter: preigu. Artikel-Nr. 127211868
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9783731512950
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