Abstract
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, γ-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.
Highlights
With the development of China, people pay more attention to environmental problems
The result shows that linear discriminant analysis (LDA) (support vector machine (SVM)) has better performance in detecting the stenches considered in this paper
This paper introduces an electronic nose to classify five kinds of stenches, which is mentioned in GBT 14675
Summary
The air pollution problem is the most concerning environmental problem in China. Exposure to pollutants such as airborne particulate matter and ozone has been associated with increases in mortality and hospital admissions due to respiratory and cardiovascular disease [1]. The triangle odor bag method is an olfactory method to measure odor concentration [2]. Two of the three bags are injected with clean air, and the other one is injected with the odor sample. The panelist needs to recognize the bag injected with the odor sample. The leader of the panel uses the empirical formula and measured data provided by at least six panelists to determine the odor concentration. With the wide application of AI, we decided to use an electronic nose and machine learning algorithms to discriminate stenches
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