The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 09, 2024

Filed:

Jun. 07, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Melih Kandemir, Stuttgart, DE;

Sebastian Gerwinn, Leonberg, DE;

Andreas Look, Stuttgart, DE;

Barbara Rakitsch, Stuttgart, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01); G06N 3/047 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G05B 13/027 (2013.01); G05B 13/048 (2013.01); G06N 3/047 (2023.01);
Abstract

A computer-implemented method of training a model for making time-series predictions of a computer-controlled system. The model uses a stochastic differential equation (SDE) comprising a drift component and a diffusion component. The drift component has a predefined part representing domain knowledge, that is received as an input to the training; and a trainable part. When training the model, values of the set of SDE variables at a current time point are predicted based on their values at a previous time point, and based on this, the model is refined. In order to predict the values of the set of SDE variables, the predefined part of the drift component is evaluated to get a first drift, and the first drift is combined with a second drift obtained by evaluating the trainable part of the drift component.


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