重庆邮电大学学报（自然科学版）2024，Vol.36Issue(2)：351-356,6.DOI:10.3979/j.issn.1673-825X.202302070025
特征提取及数据扩充的GA-LightGBM半导体质量检测方法
GA-LightGBM method of semiconductor quality inspection based on feature extraction and data expansion
摘要
Abstract
Semiconductor quality inspection data exhibit characteristics such as correlation,redundancy,and imbalance,which lead to lower efficiency in traditional classification algorithms.To address this challenge,we propose a quality inspec-tion method named GA-LightGBM(genetic algorithm-light gradient boosting machine)that leverages feature extraction and data augmentation techniques.This approach combines principal component analysis(PCA),synthetic minority oversam-pling technique(SMOTE),genetic algorithm,and LightGBM.Experimental results demonstrate that,compared to tradi-tional classification algorithms,the proposed method significantly improves the efficiency of quality inspection.关键词
质量检测/主成分分析/合成少数类过采样技术/GA-LightGBMKey words
quality inspection/principal component analysis/synthetic minority oversampling technique/genetic algorithm-light gradient boosting machine分类
信息技术与安全科学引用本文复制引用
程云飞,周丽芳,赵波,谭佳伟,王淑影..特征提取及数据扩充的GA-LightGBM半导体质量检测方法[J].重庆邮电大学学报（自然科学版）,2024,36(2):351-356,6.基金项目
吉林省重大科技专项(20210301038GX,20220301031GX) （20210301038GX,20220301031GX）
吉林省科技厅重点研发项目(20230204078YY) The Science and Technology Special Major Projects of Jilin Province(20210301038GX,20220301031GX) （20230204078YY）
The Key Research and Development Projects of Jilin Provincial Science and Technology Department(20230204078YY) （20230204078YY）
