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    杭海峰, 储炬, 叶勤, 张嗣良. 红外光谱-人工神经元网络法测定海藻培养过程中的碳酸盐浓度[J]. 华东理工大学学报(自然科学版), 2005, (4): 521-523.
    引用本文: 杭海峰, 储炬, 叶勤, 张嗣良. 红外光谱-人工神经元网络法测定海藻培养过程中的碳酸盐浓度[J]. 华东理工大学学报(自然科学版), 2005, (4): 521-523.
    Determination of Carbonate in Algae Culture Process Using Infrared Spectrum and Processing with Artificial Neural Networks[J]. Journal of East China University of Science and Technology, 2005, (4): 521-523.
    Citation: Determination of Carbonate in Algae Culture Process Using Infrared Spectrum and Processing with Artificial Neural Networks[J]. Journal of East China University of Science and Technology, 2005, (4): 521-523.

    红外光谱-人工神经元网络法测定海藻培养过程中的碳酸盐浓度

    Determination of Carbonate in Algae Culture Process Using Infrared Spectrum and Processing with Artificial Neural Networks

    • 摘要: 用傅里叶变换红外光谱法测定海藻培养液中碳酸盐浓度时,由于pH对碳酸盐特征吸收峰影响严重,本文用人工神经元网络处理红外光谱,用该方法计算得到:对标准样品的预测标准误差为NaHCO3 0.08g/L,pH值为0.12,优于偏最小二乘法的结果。用该方法对实际螺旋藻培养过程中的碳源浓度进行了测定,预测标准误差为0.65g/L。

       

      Abstract: Fourier transform infrared spectroscopy was applied to the determination of carbonate in an algae culture. Artificial neural networks was used to solve the severe influence of pH on the infrared spectra in the characteristic region. The predicted standard errors of NaHCO3 and pH value in the standard samples are 0.08 g/L and 0. 12, respectively. The results are better than that using partial least square method. This method has been proved to be an effective way to quantify the carbonate and pH value in an algae culture process.

       

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