A Regression Learning Based Process Parameter Optimization Analysis Method

Abstract

The invention discloses a process parameter optimization analysis method based on regression learning. The method includes the steps that a group of process parameters are selected, a cross-correlation matrix between working parameters and performance parameters is obtained, and the working parameters with a correlation greater than a preset value are obtained; the working parameters with the correlation greater than the preset value are divided into two groups, wherein one group is used for training, and the other group is used for verification; the performance parameters without correlationverification are divided into two groups, wherein one group includes the first performance parameters for training, and the other group includes the second performance parameters for verification; a linear regression method is adopted, data of the first working parameters and data of the first performance parameters are used as training sequences, and solution is conducted to obtain an initial coefficient matrix correlated with the first working parameters and first performance parameters; data of the second working parameters is introduced into the initial coefficient matrix to obtain data ofpredicted performance parameters, a root mean square error between the data of the predicted performance parameters and the data of the second performance parameters is obtained, and when the root mean square error is almost 0, a verified coefficient matrix is obtained.

Description

technical field [0001] The invention relates to the field of modern engineering technology, in particular to a process parameter optimization analysis method based on regression learning. Background technique [0002] In the field of modern engineering technology, there is no very accurate analytical model to describe many process parameters, but there seems to be some fixed relationship between them. In this case, we can use this method to analyze these parameters For analysis, common application scenarios include: relationship analysis between equipment working parameters and performance parameters, relationship analysis between production line quality data and operating industry parameters, etc. However, the prior art cannot effectively provide a method capable of establishing relationships among various parameters of the equipment, and thus cannot effectively estimate the project. Contents of the invention [0003] The embodiment of the present invention provides a pr...

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Problems solved by technology

[0003] The embodiment of the present invention provides a process parameter optimization analysis method based on regression learning, which solves the problem that the existing technology cannot effectively provide a model that can establish relationships between various parameters of the equipment, and thus cannot effectively estimate the project. technical issues

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