基于局部线性嵌人的制造过程多重共线性参数特征选择

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中图分类号：TH165.4

DOI：10.3969/j.issn.1004-132X.2025.06.011 开放科学（资源服务）标识码（OSID）：

Multicollinearity Parameter Feature Selection for Manufacturing Processes Based on LLEs

HU Sheng1，2 * GAO Bingbing1ZHANG XilLIU Dengji1

1.School of Mechanical Engineering and Electrical Engineering，Xi'an Polytechnic University， Xi'an，710048

2.Hubei Key Laboratory of Modern Manufacturing Quality Engineering，Hubei University of Technology，Wuhan，430068

Abstract： In manufacturing processes，a large number of parameters were easily caused to have multicollinearity，which led to problems such as inaccurate prediction of quality indicators. To address these problems，a feature selection method for multicollinear parameters in the manufacturing processes was proposed based on LLE. Firstly， the multicollinearity of the manufacturing process parameters was diagnosed，and then the multicolinearity was eliminated by using the least absolute shrinkage and selection operator（LASSO） regression. Secondly，the LLE algorithm was used to perform feature selection on the parameters after LASSO regression to obtain independent feature spaces，and they were input into the whale optimization algorithm-support vector machine（WOA-SVM） model to verify the parameter feature selection effectiveness of the proposed algorithm. Finally，the effectiveness of the proposed method was verified through case analysis. The results show that compared with the original data，the proposed method may obtain more accurate prediction results under a lower-dimensional feature space，the correlation coeficient value is up to O.97O2，and the accuracy of feature selection increases by 24.989% ：

Key words： manufacturing process； multicollinearity； local linear embedding（LLE）； feature se-lection

0 引言

制造过程复杂庞大，工序繁琐，每个工序在生产中会产生海量参数。（剩余12838字）