本文關鍵詞： 近紅外光譜 預測模型 波段篩選 偏最小二乘法 遺傳算法　出處：《南京理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：近紅外光譜分析技術是當今血糖無創(chuàng)檢測的一個研究熱點。由于近紅外光譜分析技術具有非接觸、反應靈敏、不需要試紙等特點,對糖尿病的治療具有重要的實際意義。但是通常被測樣品的近紅外光譜吸收較弱,譜峰重疊嚴重,因此選擇包含樣本信息的建模波段是近紅外光譜分析技術需要解決的核心問題。本文主要針對人眼葡萄糖濃度的近紅外光譜預測模型進行了研究。首先以葡萄糖溶液的近紅外吸收光譜為測試對象,采用傳統(tǒng)的偏最小二乘法建立基本的數(shù)學校正模型,用均方根預測誤差RMSEP和相關系數(shù)R作為評價模型的指標;針對傳統(tǒng)預測模型穩(wěn)定性較差和預測精度較低的問題,本文提出了區(qū)間組合移動窗口偏最小二乘法和改進遺傳算法,篩選出葡萄糖溶液的最優(yōu)建模波段為1567nm-1641nm;實驗配置了含有葡萄糖、尿素、抗壞血酸鹽和乳酸鹽的模擬房水溶液,采集其吸光度光譜并懫用傳統(tǒng)偏最小二乘法和本文提出的兩種方法分別建立數(shù)學校正模型,并對模型預測精度進行分析。最后基于本文提出的算法,用Matlab軟件編寫了近紅外光譜的數(shù)據(jù)處理系統(tǒng),該系統(tǒng)為科研人員提供了一個便捷的光譜分析平臺。
[Abstract]:Near-infrared spectroscopy (NIR) is a hot spot in the field of noninvasive blood glucose detection. Because NIR is non-contact, sensitive, and does not require test paper, etc. It is of great practical significance for the treatment of diabetes mellitus. However, the NIR spectra of the samples are usually weak, and the spectral peaks overlap seriously. Therefore, the selection of the modeling band containing sample information is the core problem to be solved in the near infrared spectrum analysis technology. This paper mainly focuses on the near infrared spectrum prediction model of glucose concentration in the human eye. Firstly, we study the near infrared spectrum prediction model of human eye glucose concentration. The near infrared absorption spectra of the solution were measured. The traditional partial least square method is used to establish the basic mathematical correction model, and the root-mean-square prediction error (RMSEP) and correlation coefficient R are used as the indicators of the evaluation model. In this paper, an interval combined moving window partial least-squares method and an improved genetic algorithm are proposed. The optimal modeling band of glucose solution is 1567nm-1641nm.The aqueous solution of simulated room containing glucose, urea, ascorbic acid salt and lactate is configured experimentally. The absorbance spectra were collected and the mathematical correction models were established by the traditional partial least square method and the two methods proposed in this paper, and the prediction accuracy of the model was analyzed. Finally, based on the algorithm proposed in this paper, A data processing system for near infrared spectrum is developed by using Matlab software. The system provides a convenient platform for researchers to analyze the spectrum.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O657.33;R587.1

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