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Test sample point selection method based on Gaussian process regression

A Gaussian process regression and sample point technology, applied in the field of systems engineering, can solve the problem of low efficiency in selecting test sample points, and achieve the effect of reducing the test workload, reducing the cost and improving the test efficiency.

Pending Publication Date: 2022-05-17
KUANG CHI CUTTING EDGE TECH LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The main purpose of the present invention is to provide a method for selecting test sample points based on Gaussian process regression, to solve the problem of low efficiency of test sample point selection in the prior art

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  • Test sample point selection method based on Gaussian process regression
  • Test sample point selection method based on Gaussian process regression
  • Test sample point selection method based on Gaussian process regression

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Embodiment Construction

[0035] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0036] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs.

[0037] In the present invention, unless stated otherwise, the used orientation words such as "upper, lower, top, bottom" are usually for the directions shown in the drawings, or for the parts themselves in the vertical, In terms of vertical or gravitational direction; similarly, for the convenience of understanding and description, "inner and outer" refer to the inner and outer relative to the outline of each component itself, but the above orientation words ...

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Abstract

The invention provides a test sample point selection method based on Gaussian process regression, and the method comprises the steps: determining a kernel function of a Gaussian process regression model in the process of carrying out the performance analysis of simulation data; determining an error response function; obtaining historical data of a performance test in an actual engineering problem, and generating a training data set; importing a training data set, and determining an initialized hyper-parameter of a kernel function by using a Gaussian process regression model; carrying out initialization test construction; performing iterative optimization of sampling by using a Gaussian process regression model, and selecting an optimal sampling point set; and after the iterative optimization is finished, outputting the selected optimal sampling point set. The problem of low selection efficiency of test sample points in the prior art is solved.

Description

technical field [0001] The invention relates to the technical field of system engineering, in particular to a method for selecting test sample points based on Gaussian process regression. Background technique [0002] Currently. In the field of practical engineering, the verification and confirmation of the functional performance of products or systems is a very important part of system engineering, which involves a large number of functional and performance tests. For example: wind tunnel test involving aerodynamic layout of aircraft, thrust test of rocket engine, electrical performance test of radar and other antenna systems, etc. Generally speaking, the scale of these experiments is huge, and it consumes a lot of experimental resources such as time and funds, so the selection of experimental sample points is particularly important. Common methods for selecting test sample points are as follows: [0003] 1. Traverse sampling method. That is, the response variable is ve...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06F17/18G06F17/15G06F111/10
CPCG06F30/20G06F17/18G06F17/15G06F2111/10
Inventor 刘若鹏赵治亚周鑫何洋
Owner KUANG CHI CUTTING EDGE TECH LTD