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Determination of octane number of gasoline by double ANN algorithm combined with multidimensional gas chromatography

机译:双ANN算法结合多维气相色谱法测定汽油的辛烷值

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In this paper, a double artificial neural network (ANN) algorithm has been established for calculating the octane number (ON) of gasoline from the results of multidimensional gas chromatography analysis. Multidimensional resolution column was applied to obtain the results of the detailed hydrocarbon analysis. The double ANN regression model has been established between the results of the detailed hydrocarbon analysis and the actually determined research octane number (RON). When the method was applied to determine RON of export gasoline samples, the deviation of results was about 0.5 RON compared with the standard method. The result of double ANN regression model was better than the result of partial least square (PLS) regression model. This method was easy to manipulate, and the modelling process was fast and easy to achieve. It was suitable for measuring the ON of the gasoline samples from the refinery and the export inspection.
机译:本文建立了一种双人工神经网络算法,用于从多维气相色谱分析结果中计算汽油的辛烷值(ON)。应用多维分离度色谱柱获得详细的烃分析结果。在详细的碳氢化合物分析结果与实际确定的研究辛烷值(RON)之间建立了双ANN回归模型。当该方法用于确定出口汽油样品的RON时,与标准方法相比,结果偏差约为0.5 RON。双重ANN回归模型的结果优于偏最小二乘(PLS)回归模型的结果。该方法易于操作,并且建模过程快速且易于实现。它适用于测量炼油厂的汽油样品的开度和出口检验。

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