[1]陈 艳,瞿翠玲,闫远方.香水百合头香成分色谱保留指数的人工神经网络预测[J].南京理工大学学报(自然科学版),2018,42(02):249.[doi:10.14177/j.cnki.32-1397n.2018.42.02.018]
 Chen Yan,Qu Cuiling,Yan Yuanfang.Prediction of chromatographic retention index of volatilefragrance compound in fresh flower of lilium sppby artificial neural network[J].Journal of Nanjing University of Science and Technology,2018,42(02):249.[doi:10.14177/j.cnki.32-1397n.2018.42.02.018]
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香水百合头香成分色谱保留指数的人工神经网络预测()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
42卷
期数:
2018年02期
页码:
249
栏目:
出版日期:
2018-04-30

文章信息/Info

Title:
Prediction of chromatographic retention index of volatilefragrance compound in fresh flower of lilium sppby artificial neural network
文章编号:
1005-9830(2018)02-0249-05
作者:
陈 艳瞿翠玲闫远方
徐州工程学院 化学化工学院,江苏 徐州 221111
Author(s):
Chen YanQu CuilingYan Yuanfang
School of Chemistry and Chemical Engineering,Xuzhou Institute of Technology,Xuzhou 221111,China
关键词:
香水百合 头香成分化合物 色谱保留指数 人工神经网络 定量结构-色谱保留关系
Keywords:
fresh flower of lilium spp volatile fragrance compounds chromatographic retention indices artificial neural network quantiative structure-retention relationships
分类号:
O657.63; Q949.718.23
DOI:
10.14177/j.cnki.32-1397n.2018.42.02.018
摘要:
基于分子拓扑学理论计算了香水百合头香成分35个化合物的分子连接性指数Xi电性拓扑状态指数Ej和分子电性距离矢量Mk采用最佳变量子集回归方法确定了最佳变量组合X1,E9,M9M10,并用这4个变量作为神经网络的输入层单元,建立了香水百合头香成分化合物气相色谱保留指数RI的人工神经网络模型。采用该模型对RI值进行了预测,预测结果与实验值接近,平均相对误差为1.165%。该方法成功预测了化合物的气相色谱保留指数,对于探索色谱保留机理、选择合适的分离条件等有参考价值。
Abstract:
Based on the topological theory,the molecular connectivity index Xi,the electrotopological state indexes Ej and the molecular electro-negativity distance vector Mk of 35 volatile fragrance compounds in fresh flowers of lilium spp are calculated. Using the stepwise regression method,the optimal variable combination of X1,E9,M9 and M10 is selected. The artificial neural network model of the chromatographic retention index(RI)of the titled compunds is set up by taking the preselected four parameters as the input unit and the RI is predicted by this model. The result shows that,the predicted values of the RI are close to their experimental values,and the average relative error is 1.165%. This method can predict the gas chromatographic retention index of the compounds successfully,and it is helpful for selecting the experimental separation condition and exploring the mechanism of chromatographic retention.

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备注/Memo

备注/Memo:
收稿日期:2017-03-13 修回日期:2017-04-18
基金项目:国家自然科学基金(21272095)
作者简介:陈艳(1968-),女,硕士,教授,主要研究方向:有机合成及物质构效关系,E-mail:chenyan681110@126.com。
引文格式:陈艳,瞿翠玲,闫远方. 香水百合头香成分色谱保留指数的人工神经网络预测[J]. 南京理工大学学报,2018,42(2):249-253.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2018-04-30