文献类型：期刊文献

英文题名：Five Typical Stenches Detection Using an Electronic Nose

作者：Jiang, Wei[1];Gao, Daqi[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200030, Peoples R China

年份：2020

卷号：20

期号：9

外文期刊名：SENSORS

收录：;EI(收录号：20202108686165);WOS:【SCI-EXPANDED(收录号:WOS:000537106200078)】；

语种：英文

外文关键词：stenches detection; odor concentration; electronic nose; machine learning algorithm

摘要：This paper deals with the classification of stenches, which can stimulate olfactory organs to discomfort people and pollute the environment. In China, the triangle odor bag method, which only depends on the state of the panelist, is widely used in determining odor concentration. In this paper, we propose a stenches detection system composed of an electronic nose and machine learning algorithms to discriminate five typical stenches. These five chemicals producing stenches are 2-phenylethyl alcohol, isovaleric acid, methylcyclopentanone, gamma -undecalactone, and 2-methylindole. We will use random forest, support vector machines, backpropagation neural network, principal components analysis (PCA), and linear discriminant analysis (LDA) in this paper. The result shows that LDA (support vector machine (SVM)) has better performance in detecting the stenches considered in this paper.