基于太赫兹时域光谱和PCA-SVM 算法的甜蜜素含量分析 |
投稿时间:2024-03-04 修订日期:2024-03-13 点此下载全文 |
引用本文:王睿璇,谭智勇,曹俊诚.基于太赫兹时域光谱和PCA-SVM 算法的甜蜜素含量分析[J].红外,2024,45(9):44~52 |
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基金项目:国家自然科学基金项目(61927813; 61991432) |
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中文摘要:光谱分析是研究太赫兹(THz)辐射与物质相互作用的重要手段。采用全光纤式THz时域光谱(THz Time-Domain Spectroscopy, THz-TDS)系统测试了不同含量甜蜜素样品的透过率光谱,发现甜蜜素的特征吸收峰位置在1.4 THz和1.7 THz附近;采用主成分分析结合支持向量机(PCA-SVM)的方法建立了甜蜜素含量回归模型,然后将其预测结果与遗传算法结合偏最小二乘(GA-PLS)模型进行分析比较,并引入决定系数(R2)和预测均方根误差(RMSE)来评价建模效果,对以10%含量梯度制作的样品集进行检测。研究结果表明,采用PCA-SVM、SVM和GA-PLS方法建立的预测模型的RMSE分别为1.885%、1.926%和2.432%。因此,PCA-SVM方法的预测效果最优,且预测数据与实际数据均表现出良好的相关性,获得了效果良好的含量回归预测模型,为甜蜜素含量的检测与分析提供了一种有效手段。 |
中文关键词:太赫兹时域光谱 主成分分析 支持向量机 含量回归预测模型 |
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Analysis of Saccharin Content Based on Terahertz Time-Domain Spectroscopy and PCA-SVM Algorithm |
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Abstract:Spectral analysis is an important means of studying the interaction between THz radiation and matter. The transmittance spectra of samples with different levels of saccharin are tested using an all-fiber THz-TDS system, and it is found that the characteristic absorption peaks of saccharin are located around 1.4 THz and 1.7 THz. PCA-SVM method is used to establish the regression model of saccharin content, and the prediction results are analyzed and compared with the GA-PLS model. Correlation coefficients and RMSE are introduced to evaluate the modeling effect, and the sample set made with a 10% content gradient is tested. The research results show that the RMSE of the prediction models established using PCA-SVM, SVM and GA-PLS methods are 1.885%, 1.926% and 2.432%, respectively. Therefore, the PCA-SVM method has the best prediction performance, and the predicted data show a good correlation with the actual data. A content regression prediction model with good performance is obtained, which provides an effective means for the detection and analysis of saccharin content. |
keywords:THz-TDS principal component analysis support vector machine content regression prediction model |
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