西华大学学报（自然科学版）2017，Vol.36Issue(3)：57-64,8.DOI:10.3969/j.issn.1673-159X.2017.03.010
基于SOM-PCA-RBF的过程质量预测与整体调优
Process Quality Prediction and Overall Tuning Method Based on SOM-PCA-RBF
摘要
Abstract
In order to improve process output quality,a method for process quality prediction and multi-factor integrated optimizing is proposed.This method combines self-organized map neural network (SOMNN),principal component analysis (PCA) and radial basis function neural network (RBFNN).SOMNN is used to classify the process data.PCA is used to evaluate the classified data and establish the process factors repository.RBFNN is used to establish the process prediction model,determine the conformity of the process output quality by predicting,and propose the scheme for multi-factor integrated optimizing.The case analysis result shows that the method is effective and can achieve preventive quality improvement.关键词
质量改进/过程优化/SOM神经网络/主成分分析/RBF神经网络Key words
quality improvement/process optimization/self-organized map neural networks/principal component analysis/radial basis function neural networks分类
信息技术与安全科学引用本文复制引用
陈昌华,徐文杰,姚进..基于SOM-PCA-RBF的过程质量预测与整体调优[J].西华大学学报（自然科学版）,2017,36(3):57-64,8.基金项目
四川省科技计划项目(2017GZ0187,2017GZ0358) （2017GZ0187,2017GZ0358）
西华大学校重点项目(zw1311543). （zw1311543）
