A novel THz spectroscopy recognition method for transgenic organisms based on APSO combined with SVM
- 作者: Li T.J.1, Liu J.J.2, Shao G.F.3, Fan L.L.2
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隶属关系:
- School of Automation
- School of Electrical Engineering
- Department of Automation
- 期: 卷 120, 编号 4 (2016)
- 页面: 660-665
- 栏目: Geometrical and Applied Optics
- URL: https://ogarev-online.ru/0030-400X/article/view/164698
- DOI: https://doi.org/10.1134/S0030400X16040159
- ID: 164698
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详细
Currently, the transgenic products detection methods are mostly based on visible/near-infrared light spectrum. In addition, it is hard to set up the parameters in the support vector machine (SVM) model and there is a large amount of calculation on spectrum data. To solve these problems, this paper proposed an algorithm based on terahertz (THz) spectrum and SVM using adaptive particle swarm optimize (APSO-SVM) for building up the classifications of transgenic cotton seed. To conduct the transgenic cotton seed classification, within the wavelength region 150 μm—3 mm, the THz spectrums are first sampled from 165 samples of three newest transgenic cotton seeds. Then, the 165 transgenic cotton seeds are recognized based on the APSO-SVM. Experiment results indicate that the total recognition rate is up to 97.3%, which prove that the THz spectrum combined with APSO-SVM can provide a reliable, rapid, simple and nondestructive detection method for transgenic cotton seed.
作者简介
T. Li
School of Automation
Email: liujianjun8888@hotmail.com
中国, Çhongqing, 400044
J. Liu
School of Electrical Engineering
编辑信件的主要联系方式.
Email: liujianjun8888@hotmail.com
中国, Jiujiang, 332005
G. Shao
Department of Automation
Email: liujianjun8888@hotmail.com
中国, Xiamen, 361005
L. Fan
School of Electrical Engineering
Email: liujianjun8888@hotmail.com
中国, Jiujiang, 332005
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