Application of Kohonen and BP Neural Networks to Simultaneous Determination of Tungsten and Molybdenum
WANG Jin-ping1,SUN Xiao-bo1,LI Jing-hui2,GAO Li-rang2,NIU Chun-ji3
1. College of Science, Laiyang Agricultural University，Qingdao 266109, China 2. College of Chemical Engineering, Anshan University of Science and Technology，Anshan 114002, China 3. Changchun Institute of Applied Chemistry, Chinese Academy of Sciences，Changchun 133002, China
Abstract：BP artificial neural networks combined with Kohonen networks were used for the simultaneous determination of tungsten and molybdenum by spectrophotometry. First, the topology structure of Kohonen artificial neural networks was studied, and applied to the wavelength selection of the overlapped spectra of tungsten and molybdenum. Then the most informative wavelengths were selected from the full spectra, and absorbance values were used as the optimal input sets of the three-layer BP neural networks. Compared with the routine method of wavelength selection, the results prove that using Kohonen networks to select the most informative wavelengths can optimize the input layer of BP-ANN, and the prediction ability of BP-ANN is improved. So Kohonen networks can be used as a tool for wavelength selection.
王进平1,孙晓波1,李井会2,高礼让2,牛春吉3 . Kohonen网络与BP网络用于钨和钼的同时测定[J]. 光谱学与光谱分析, 2006, 26(12): 2319-2322.
WANG Jin-ping1,SUN Xiao-bo1,LI Jing-hui2,GAO Li-rang2,NIU Chun-ji3 . Application of Kohonen and BP Neural Networks to Simultaneous Determination of Tungsten and Molybdenum . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(12): 2319-2322.
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