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人工神经网络用于近红外光谱预测汽油辛烷值
引用本文:高俊,姚成,章俊.人工神经网络用于近红外光谱预测汽油辛烷值[J].分析科学学报,2006,22(1):71-73.
作者姓名:高俊  姚成  章俊
作者单位:1. 南京工业大学理学院,南京,210009
2. 南京工业大学信息工程学院,南京,210009
摘    要:本文对BP人工神经网络(ANN)方法在汽油的辛烷值与其近红外光谱光谱吸光度的关系之间进行关联预报方面进行了研究。采用35个汽油实际样本数据,建立了利用汽油的近红外光谱光谱吸光度预测汽油辛烷值的BP人工神经网络模型。对所有辛烷值的计算结果与实测值进行了比较,得到的预测值与实测值计算误差小于1.55%。

关 键 词:BP神经网络  汽油辛烷值  近红外光谱
文章编号:1006-6144(2006)01-0071-03
收稿时间:2004-06-21
修稿时间:2004-11-12

Application of Artificial Neural Network for the Prediction of Gasoline Octane Number by Near-infrared Spectroscopy
GAO Jun,YAO Cheng,ZHANG Jun.Application of Artificial Neural Network for the Prediction of Gasoline Octane Number by Near-infrared Spectroscopy[J].Journal of Analytical Science,2006,22(1):71-73.
Authors:GAO Jun  YAO Cheng  ZHANG Jun
Institution:1 College of Sciences, Nanjing University of Technology, Nanjing 210009;2 College of Information Science and Engineering, Nanj ing University of Technology , Nanjing 210009
Abstract:The relation between the gasoline octane number and the near-infrared absorbence of gasoline by using BP artificial neural network for the prediction of gasoline octane number was studied in this article.35 near-infrared spectroscopy data,were used to construct the BP artificial neural network model for the prediction of gasoline octane number.All the predicted values by the model have been compared with the practical values,and the error was less than 1.55%.
Keywords:BP neural network  Gasoline  Octance number  Near infrared spectrum  
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