US 12,423,554 B2
Method for determining safety-critical output values by way of a data analysis device for a technical entity
Mathis Brosowsky, Stuttgart (DE)
Assigned to Dr. Ing. h.c. F. Porsche Aktiengesellschaft, (DE)
Filed by Dr. Ing. h.c. F. Porsche Aktiengesellschaft, Stuttgart (DE)
Filed on Oct. 4, 2021, as Appl. No. 17/492,777.
Claims priority of application No. 10 2020 127 051.8 (DE), filed on Oct. 14, 2020.
Prior Publication US 2022/0114416 A1, Apr. 14, 2022
Int. Cl. G06N 3/04 (2023.01); G06N 3/08 (2023.01)
CPC G06N 3/04 (2013.01) [G06N 3/08 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A method for determining safety-critical output values (y1, y2, . . . , yn) by way of a data analysis device for a technical entity, said method comprising:
receiving data and/or measured values for the entity and/or surroundings of the entity by way of the data analysis device, wherein the data/measured values describe at least one state and/or at least one feature of the entity and/or the surroundings of the entity and constitute input values (x);
processing the input values (x) by way of the data analysis device using a software application in order to determine at least one first output value (y1), said processing step comprising the following substeps:
(i) using a neural network having a plurality of layers (hθ(x)) with first learnable parameters (θ);
(ii) modifying the last layer or an additional layer of the neural network using a function (φ) so that at least one first output value (y1) of said output values (y1, y2, . . . , yn) is located within a defined value range (C(s)) of at least one target parameter (s); and
(iii) determining the target parameter (s) and/or the value range (C(s)) of the target parameter (s) using further additional layers (kβ(x)) of the neural network with second learnable parameters (β).