Method, apparatus and device for optimizing process parameter, and storage medium

Abstract

The present application pertains to the field of data processing technology, specifically relates to a method, apparatus and device for optimizing a process parameter and a storage medium, which includes: using a first weight parameter of a pre-trained support vector regression model for a manufacturing equipment as an iterative initial value, and calculating a second weight parameter of a support vector regression model using an online proximal gradient algorithm based on training data; obtaining an optimized support vector regression model by updating the first weight parameter of the pre-trained support vector regression model to the second weight parameter; inputting a first process parameter of the manufacturing equipment into the optimized support vector regression model to obtain a first detection parameter output by the optimized support vector regression model; and calculating, according to the first process parameter and the first detection parameter, a target process parameter for the manufacturing equipment.