A new method for rapid detection of pesticide residues based on multi⁃sensor optimization

被引：0
作者：
Li P.-Z. [1 ,2 ]
Zhao S.-S. [1 ]
Weng X.-H. [3 ]
Jiang X.-M. [4 ]
Cui H.-B. [4 ]
Qiao J.-L. [4 ]
Chang Z.-Y. [5 ,6 ]
机构：
[1] College of Mathematics, Jilin University, Changchun
[2] School of Artificial Intelligence, Jilin University, Changchun
[3] School of Mechanical and Aerospace Engineering, Jilin University, Changchun
[4] College of Horticulture, Jilin Agricultural University, Changchun
[5] Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun
[6] College of Biological and Agricultural Engineering, Jilin University, Changchun
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2022年 / 52卷 / 08期
关键词：
CatBoost; electronic nose; feature selection; multi-sensor; pesticide science;
D O I：
10.13229/j.cnki.jdxbgxb20210176
中图分类号：
学科分类号：
摘要：
A sensor array optimization strategy based on CatBoost algorithm was proposed. Using the self-developed electronic nose testing system based on bionic olfaction，the residual trichlorfon on dandelion was detected，the response characteristic information of the dandelion sample was extracted ，and the multi-characteristic data fusion on the sensor array was performed. The CatBoost algorithm was used to perform feature selection on the data matrix. The number of optimized sensors was reduced from 12 to 3，the accuracy rate was increased from 91.69% to 98.03%，and the number of features was reduced by 88%，which was better than correlation coefficient，recursive elimination and other commonly used algorithms. The problem of multiple sensors and data redundancy was solved，and the detection accuracy was greatly improved. The results show that the use of CatBoost algorithm in the detection of trichlorfon residues on dandelion can improve the identification ability of the electronic nose. © 2022 Editorial Board of Jilin University. All rights reserved.
引用
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页码：1951 / 1956
页数：5
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