Application of Neural Network in the Analysis of Near-Infrared Spectra

Ping Zuo, Shichun Pang, Xue Feng, Ya Gao, Dandan Qin
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Abstract

The main problem in the spectrum analysis technology is the difficulty in locating the target which will affect the predication and the analysis. How to choose the right mathematic model becomes the key point in the spectrum analysis. This paper designs the practical manual neural network model to locate the target and predicate. This paper uses error backward direction propagation calculation method and establishes three-layer neural network to solve the problems such as the spectrum peaks overlap seriously and noise is big in the spectrum analysis. When the quantity of samples to be located the target is significant, employ manual neural network method to analyze and discuss the corn's protein content and near-infrared spectrum. By analyzing the experimental result this paper concludes that manual neural network method performs better than linear regression method and partial least-squares method and obtains ideal result.
神经网络在近红外光谱分析中的应用
频谱分析技术存在的主要问题是目标定位困难,这将影响预测和分析。如何选择合适的数学模型成为频谱分析的关键。本文设计了实用的人工神经网络模型来定位目标和谓词。本文采用误差反向传播计算方法,建立三层神经网络,解决了频谱分析中频谱峰重叠严重、噪声大等问题。当待定位目标样品数量较大时,采用人工神经网络方法对玉米的蛋白质含量和近红外光谱进行分析讨论。通过对实验结果的分析,得出人工神经网络方法优于线性回归方法和偏最小二乘方法,并取得了理想的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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