摘要
电子鼻广泛应用于诸多领域,在不同领域中电子鼻传感器阵列的构成不同。由于中药气味的复杂性和特殊性,在中药鉴别分析中,需建立阵列优化法、筛选专属最佳阵列。采用法国Alpha MOS公司的α-FOX3000电子鼻对姜科常用10味中药进行气味检测,基于逐步判别分析法和聚类分析结合典型指标筛选法,建立了MOS传感器阵列的优化法。同时针对优化前后的数据,分别采用主成分分析、Fisher判别分析和随机森林算法进行了对比研究。结果表明,优化后的阵列不仅保留了原始阵列的有效信息,而且在一定程度上剔除了冗余信息、提高了识别效率。随机森林分类器计算结果表明:最佳阵列为逐步判别分析筛选的S1,S2,S5,S6,S8,S12组合而成,此阵列优化法有效、可行;为电子鼻在中药鉴别中MOS传感器阵列的优化提供思路与方法参考。
[ Abstract ] Optimization of sensor array is a significant topic in the application of electronic nose (EN). Stepwise discriminant analysis and cluster analysis combining with screening of typical index were employed to optimize the original array in the classification of 100 samples from 10 kinds of traditional Chinese medicine based on a-FOX3000 EN. And the identification ability was evaluated by three algorithm including principle component analysis, Fisher discriminant analysis and random forest. The results showed that the identification ability of EN was improved since not only the effective information was maintained but also the redundant one was elimina- ted by the optimized array. The optimized method was eventually established, it was accurate and efficient. And the optimized array was built up, that is, S1 ,S2 ,S5 ,S6 ,S8 ,S12.
出处
《中国中药杂志》
CAS
CSCD
北大核心
2013年第2期161-166,共6页
China Journal of Chinese Materia Medica
基金
北京中医药大学自主选题项目(JYB22-XS041)
关键词
电子鼻
中药材
传感器阵列
随机森林
electronic nose
traditional Chinese medicine
sensor array
random forest