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Establish an Artificial neural Networks Model to make Quantitative Analysis about the Capillary Electrophoresis Spectrum

机译:建立人工神经网络模型,对毛细管电泳谱进行定量分析

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Simulating the overlapping capillary electrophoresis spectrogram under the dissimilar conditions by the computer system, Choosing the overlapping capillary electrophoresis spectrogram simulated under the different conditions, processing the data to compose a neural network training regulations, Applying the artificial neural networks method to make a quantitative analysis about the multi-component in the overlapping capillary electrophoresis spectrogram,Using: Radial direction primary function neural network model and multi-layered perceptron neural network model. The findings indicated that, along with the increasing of the capillary electrophoresis spectrogram noise level, the related components' ability of the two kinds of the overlapping capillary electrophoresis spectrogram by neural network model quantitative analysis drop down. Along with the increasing of the capillary electrophoresis spectrogram's total dissociation degree, the multi-layered perceptron neural network model to the related components' ability of the overlapping capillary electrophoresis spectum by quantitative analysis raise up.
机译:模拟由计算机系统中的不同的条件下的重叠毛细管电泳谱图,选择重叠毛细管电泳谱图模拟在不同条件下,处理所述数据以组成一个神经网络训练法规,应用人工神经网络的方法来做出关于一个定量分析重叠毛细管电泳谱图中的多组分,使用:径向初级函数神经网络模型和多层透析器神经网络模型。结果表明,随着毛细管电泳谱图噪声水平的增加,神经网络模型的两种重叠毛细管电泳谱图的相关组分能力定量分析下降。随着毛细管电泳谱图的总解离程度的增加,通过定量分析升起,多层的感知毛细血管神经网络模型与重叠毛细管电泳壁的相关组分的能力。

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