高等学校化学学报

高等学校化学学报 ›› 1999, Vol. 20 ›› Issue (S1): 434.

• Chemometrics • 上一篇    下一篇

Study of Retention Index of GC of Alkane by using Novel Molecular Distance-Edge Vector (λ)and Functional-Enhanced Net

YIN Chun-Sheng1, REN Qin1,2, PAN Zhong-Xiao1, LI Zhi-Liang1,2, ZHANG Mao-Sena1   

  1. 1. Department of Applied Chemistry, USTC. Hefei 230026, P. R. China;
    2. College of Chemistry and Chemical Engineering, ICP, Hunan University, Changsha 410082
  • 出版日期:1999-12-31 发布日期:1999-12-31

Study of Retention Index of GC of Alkane by using Novel Molecular Distance-Edge Vector (λ)and Functional-Enhanced Net

YIN Chun-Sheng1, REN Qin1,2, PAN Zhong-Xiao1, LI Zhi-Liang1,2, ZHANG Mao-Sena1   

  1. 1. Department of Applied Chemistry, USTC. Hefei 230026, P. R. China;
    2. College of Chemistry and Chemical Engineering, ICP, Hunan University, Changsha 410082
  • Online:1999-12-31 Published:1999-12-31

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摘要：

The Functional-Enhanced net (FEN), a newly developed single-layer neural network, without hidden layer, is introduced and used to predict the retention indices of gas chromatography (GC) of alkane compounds in straight-run gasoline,with novel molecular distance-edge (MDE) vector (λ)in alkanes.

Abstract:

The Functional-Enhanced net (FEN), a newly developed single-layer neural network, without hidden layer, is introduced and used to predict the retention indices of gas chromatography (GC) of alkane compounds in straight-run gasoline,with novel molecular distance-edge (MDE) vector (λ)in alkanes.

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