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.
摘要:
A method for generating an allowed input data trajectory for a physical system to be tested or measured, including providing an input data trajectory in an input data space; determining an allowed operating range; and replacing at least one segment of the provided input data trajectory, which is outside of the allowed operating range, by a trajectory segment within the allowed operating range, in order to obtain the allowed input data trajectory.