METHOD AND DEVICE FOR CREATING A NONPARAMETRIC, DATA-BASED FUNCTION MODEL

摘要

A method for ascertaining a nonparametric, data-based function model, in particular a Gaussian process model, using provided training data, the training data including a number of measuring points which are defined by one or multiple input variables and which each have assigned output values of at least one output variable, including: selecting one or multiple of the measuring points as certain measuring points or adding one or multiple additional measuring points to the training data as certain measuring points; assigning a measuring uncertainty value of essentially zero to the certain measuring points; and ascertaining the nonparametric, data-based function model according to an algorithm which is dependent on the certain measuring points of the modified training data and the measuring uncertainty values assigned in each case.

主权项

1. A method for ascertaining a nonparametric, data-based function model, the method comprising:
selecting one or multiple ones of the measuring points as certain measuring points or adding one or multiple ones of additional measuring points to provided training data as certain measuring points, wherein the nonparametric, data-based function model is ascertained using the provided training data, the training data including a number of measuring points which are defined by one or multiple input variables and which each have assigned output values of at least one output variable; assigning a measuring uncertainty value of essentially zero to the certain measuring points; and ascertaining the nonparametric, data-based function model according to an algorithm which is dependent on the certain measuring points of the modified training data and the measuring uncertainty values assigned in each case.