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Target test model training method and device

A technology for testing models and targets, applied in the field of neural networks, can solve problems such as the influence of equipment temperature, achieve the effect of improving accuracy and reducing influence

Pending Publication Date: 2021-03-12
BEIJING AEROSPACE MEASUREMENT & CONTROL TECH
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the embodiment of the present application is to provide a training method and device for a target test model to solve the problem that equipment is affected by temperature

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  • Target test model training method and device
  • Target test model training method and device
  • Target test model training method and device

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Embodiment Construction

[0059] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, but not all of them. Based on the embodiments in the present application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present application.

[0060] In the following description, use of suffixes such as 'module', 'part' or 'unit' for denoting elements is only for facilitating the description of the present application and has no specific meaning by itself. Therefore, "module" and "component" may be mixedly used.

[0061] In order to solve the problems mentioned in the backgr...

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Abstract

The invention provides a target test model training method and device, and belongs to the technical field of neural networks. The method comprises the following steps: inputting normalized numerical values of a sample temperature value and a sample pressure value into an initial test model, and obtaining a test pressure value output by the initial test model; determining a current fitness value ofan individual in a current group of the initial test model, the individual being a current weight value and a current threshold value of the initial test model, and an error value between the test pressure value and a preset pressure value under the current weight value and the current threshold value being inversely proportional to the current fitness value; if the current fitness value does notmeet the termination condition, performing iterative genetic operation on the individual of the initial test model until the current fitness value of the individual meets the termination condition toobtain a target weight and a target threshold; and taking the initial test model containing the target weight and the target threshold as a target test model. The influence of the temperature on thepressure can be reduced, and the precision of pressure measurement is improved.

Description

technical field [0001] The present application relates to the technical field of neural networks, in particular to a training method and device for a target test model. Background technique [0002] Pneumatic pressure scanning test is the product of the combination of sensor technology and electronic technology, mainly for wind tunnel test, aero engine test, automobile test and other scientific and technological fields. By measuring the pressure distribution on the surface of the object to be measured, it provides loads for the calculation of structural strength, provides a design basis for the study of the aerodynamic characteristics of the object to be measured, and is also an important means to verify the accuracy of the numerical calculation method. Through multi-point pressure distribution measurement, it is possible to determine the position of the minimum pressure point on the surface to be tested, the position of the shock wave, whether the airflow is separated, etc....

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Application Information

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IPC IPC(8): G06F30/27G06K9/62G06N3/00G06N3/04G06N3/12
CPCG06F30/27G06N3/126G06N3/006G06N3/045G06F18/214
Inventor 杨敬贾召会曹宇蔄元臣郑磊张永武
Owner BEIJING AEROSPACE MEASUREMENT & CONTROL TECH
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