Development of a modular Knowledge-Discovery Framework based on Machine Learning

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,...

Mô tả đầy đủ

Đã lưu trong:

Chi tiết về thư mục
Tác giả chính:	Botticelli, Massimiliano
Định dạng:	Online
Ngôn ngữ:	Tiếng Anh
Được phát hành:	KIT Scientific Publishing 2023
Những chủ đề:	Gasoline Direct Injection; Data-Driven Development; Machine Learning Application; Datengetriebene Entwicklung; Anwendung des Maschinellen Lernens; Knowledge Discovery; Benzin-Direkteinspritzung thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials
Truy cập trực tuyến:	https://library.oapen.org/handle/20.500.12657/63852
Các nhãn:	Thêm thẻ Không có thẻ, Là người đầu tiên thẻ bản ghi này!

Miêu tả
Tóm tắt:	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.

Development of a modular Knowledge-Discovery Framework based on Machine Learning

Những quyển sách tương tự