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

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

Show other versions (1)

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,...

Full description

Saved in:
Bibliographic Details
Main Author: Botticelli, Massimiliano (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2023
Series:Reihe Informationsmanagement im Engineering Karlsruhe 2
Subjects:
Mechanical engineering & materials
Gasoline Direct Injection; Data-Driven Development; Machine Learning Application; Datengetriebene Entwicklung; Anwendung des Maschinellen Lernens; Knowledge Discovery; Benzin-Direkteinspritzung
Online Access:OAPEN Library: download the publication
OAPEN Library: description of the publication
Tags: Add Tag
No Tags, Be the first to tag this record!
Show all versions (2)

Similar Items