基于混合机器学习法的太赫兹波鉴别草种的研究 下载: 589次
Identification of a Grass Species Using a Terahertz Wave Based on Hybrid Machine Learning Method
1 中国石油大学(北京)理学院,北京 102249
2 内蒙古自治区草原工作站,内蒙古 呼和浩特 010020
图 & 表
图 1. THz-TDS系统示意图
Fig. 1. Schematic of THz-TDS system
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图 2. 5种牧草沙打旺样品的太赫兹时域、频域光谱图。(a)时域光谱图;(b)频域光谱图
Fig. 2. Terahertz time and frequency domain spectral waveforms of five Astragalus adsurgens Pall. seeds. (a) Terahertz time domain spectral waveforms; (b) terahertz frequency domain spectral waveforms
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图 3. 5种牧草沙打旺样品的吸收系数图谱
Fig. 3. Absorption coefficient spectra of five Astragalus adsurgens Pall. seeds
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图 4. 5种牧草沙打旺样品的平均吸收系数和标准差
Fig. 4. Average absorption coefficient and standard deviation of five Astragalus adsurgens Pall. seeds
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图 5. 5种牧草沙打旺样品的折射率谱图
Fig. 5. Refractive index spectra of five Astragalus adsurgens Pall. seeds
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表 15种牧草沙打旺种子的相关信息
Table1. Relevant information of five samples of Astragalus adsurgens Pall. seeds
Number | Name | Place of origin | Year |
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Sample 1 | Sha Da Wang 1 | Helin | 2010 | Sample 2 | Sha Da Wang 2 | Helin | 2012 | Sample 3 | Sha Da Wang 3 | Helin | Before 2010 | Sample 4 | Sha Da Wang 4 | Helin | 2016 | Sample 5 | Sha Da Wang 5 | Helin | 2016 |
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表 2随机森林模型的分类结果
Table2. Classification results of RF model
No. | Classification accuracy of all kinds of samples/% | Classification accuracy of five samples/% |
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Sample 1 | Sample 2 | Sample 3 | Sample 4 | Sample 5 |
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Average classification accuracy/% | 81.60 | 85.00 | 86.10 | 81.90 | 90.90 | 85.00 | 1 | 75 | 100 | 86 | 67 | 86 | 83.30 | 2 | 80 | 89 | 86 | 80 | 100 | 86.70 | 3 | 91 | 60 | 100 | 86 | 67 | 83.30 | 4 | 60 | 100 | 100 | 67 | 86 | 83.30 | 5 | 80 | 67 | 67 | 100 | 100 | 83.30 | 6 | 75 | 100 | 89 | 80 | 100 | 86.70 | 7 | 100 | 63 | 100 | 100 | 80 | 86.70 | 8 | 80 | 100 | 78 | 71 | 100 | 83.30 | 9 | 75 | 85 | 75 | 88 | 100 | 86.70 | 10 | 100 | 83 | 80 | 80 | 90 | 86.70 |
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表 3主成分特征向量
Table3. Eigenvector of principle component
Component | Eigenvector |
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Eigenvalue | Variance contribution rate/% | Cumulative variance contribution rate/% |
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1 | 84.29 | 95.79 | 95.79 | 2 | 3.214 | 3.650 | 99.44 | 3 | 0.2125 | 0.2400 | 99.68 |
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表 4PCA-RF 模型的分类结果
Table4. Classification results of PCA-RF model
No. | Classification accuracy of all kinds of samples/% | Classification accuracy of five samples/% |
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Sample 1 | Sample 2 | Sample 3 | Sample 4 | Sample 5 |
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Average classification accuracy/% | 94.20 | 92.10 | 88.30 | 97.00 | 91.40 | 91.20 | 1 | 80 | 100 | 100 | 90 | 100 | 93.30 | 2 | 100 | 83 | 89 | 80 | 100 | 90.00 | 3 | 100 | 83 | 75 | 100 | 100 | 93.30 | 4 | 100 | 80 | 83 | 100 | 75 | 90.00 | 5 | 100 | 100 | 80 | 100 | 71 | 90.00 | 6 | 86 | 100 | 83 | 100 | 100 | 93.30 | 7 | 86 | 75 | 100 | 100 | 100 | 90.00 | 8 | 90 | 100 | 100 | 100 | 100 | 96.70 | 9 | 100 | 100 | 87 | 100 | 88 | 90.00 | 10 | 100 | 100 | 86 | 100 | 80 | 93.30 |
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王芳, 张春红, 赵景峰, 哈斯巴特尔, 张玉. 基于混合机器学习法的太赫兹波鉴别草种的研究[J]. 激光与光电子学进展, 2021, 58(3): 0330001. Wang Fang, Zhang Chunhong, Zhao Jingfeng, Ha Sibateer, Zhang Yu. Identification of a Grass Species Using a Terahertz Wave Based on Hybrid Machine Learning Method[J]. Laser & Optoelectronics Progress, 2021, 58(3): 0330001.