Method and device for machine learning in a computing unit

US11488035B2 · kind B2 · utility

Assignee

• Siemens Aktiengesellschaft · DE

Inventor

• Daniel SCHALL · Hollabrunn, AT

Key dates

• Filing date: Nov 8, 2017
• Grant date: Nov 1, 2022
• Expiry date: Nov 1, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/045
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method and device for machine learning wherein, in order to create favorable method conditions, an at least first machine learning model is trained via an at least first data set, a second machine learning model is trained via a second data set, an at least first prediction data set is formed via the trained at least first machine learning model, a second prediction data set is formed via the trained second machine learning model, a linking machine learning model is trained at least via the first prediction data set and the second prediction data set, a third prediction data set is formed via the linking machine learning model, and controlled variables for controlling a control apparatus are formed at least via the third prediction data set, such that the demand for computing power is reduced and the prediction accuracy and control accuracy are increased.