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Neural Network Solution of an Inverse Problem in Raman Spectroscopy of Multi-component Solutions of Inorganic Salts

机译:无机盐多组分溶液拉曼光谱逆问题神经网络解

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The paper presents a study into several aspects of solution of the inverse problem on determination of concentrations of components in a multi-component water solution of inorganic salts by processing Raman spectra of the solutions by perceptron type artificial neural networks. The studied aspects are: (1) determination of the optimal architecture of a multi-layer perceptron, (2) influence of the input dimensionality reduction by aggregation of adjacent spectral channels on the error of problem solution. The results are compared for two data arrays including spectra of solutions of: (1) 5 salts composed of 10 different ions (salt determination problem), and (2) 10 salts composed of 10 different ions (ion determination problem).
机译:本文介绍了通过通过Perceptron型人工神经网络加工溶液的拉曼光谱法测定无机盐的多组分水溶液中组分浓度的若干方面的研究。 所研究的方面是:(1)确定多层Perceptron的最佳架构,(2)通过对问题解决方案误差的相邻光谱通道的聚合来对输入维度降低的影响。 将结果与两个数据阵列进行比较,包括:(1)5种不同离子(盐测定问题)组成的5种盐,(2)10种不同离子组成的盐(离子测定问题)组成。

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