安徽大学学报（自然科学版）2026，Vol.50Issue(2)：58-65,8.DOI:10.3969/j.issn.1000-2162.2026.02.008
基于协同策略模拟退火的呼气试验人群分类识别方法
Population classification and recognition method for breath test based on collaborative strategy simulated annealing
李军炜 1葛殿龙 2陆燕 2储焰南3
作者信息
- 1. 安徽大学物质科学与信息技术研究院,安徽 合肥 230601||中国科学院合肥物质科学研究院健康与医学技术研究所,安徽 合肥 230031
- 2. 中国科学院合肥物质科学研究院健康与医学技术研究所,安徽 合肥 230031||中国科学院合肥肿瘤医院,安徽 合肥 230031
- 3. 安徽大学物质科学与信息技术研究院,安徽 合肥 230601||中国科学院合肥物质科学研究院健康与医学技术研究所,安徽 合肥 230031||中国科学院合肥肿瘤医院,安徽 合肥 230031
- 折叠
摘要
Abstract
To address the online classification diagnosis problem in breath test population classification and identification,a simulated annealing optimization algorithm based on a dual-coordinated strategy of cooling mechanism and variable iteration count is proposed to achieve breath test population classification and identification.In this algorithm,the cooling mechanism employs a sine function for small fluctuation cooling,thereby enhancing the global search capability;the variable iteration count utilizes an iteration count increase mechanism combined with an upper limit setting to balance the algorithm's search capability and speed.To verify the effectiveness of this method,breath classification experiments were conducted before and after rinsing the mouth.The results showed that the accuracy rate of the test set reached 92.3％,which is 3.8％higher than that obtained by the commercially available OPLS-DA+Wilcoxon software for discriminant analysis.关键词
分类诊断/人工智能/呼气分析/色谱质谱/模拟退火算法Key words
classification diagnosis/artificial intelligence/breath analysis/chromatography-mass spectrometry/simulated annealing algorithm分类
信息技术与安全科学引用本文复制引用
李军炜,葛殿龙,陆燕,储焰南..基于协同策略模拟退火的呼气试验人群分类识别方法[J].安徽大学学报（自然科学版）,2026,50(2):58-65,8.
