Chinese Journal of Magnetic Resonance ›› 1997, Vol. 14 ›› Issue (5): 403-412.

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NEURAL NETWORK APPLIED TO THE STUDY OF CHEMICAL SHIFT OF 13C NMR SPECTROSCOPY IN ALKANES WITH A NOVEL MOLECULAR DISTANCEEDGE VECTOR (λ)

Hu Fang1, Liu Shushen1,2, Yu Banmei3, Peng Shengyang3, Mo Liyu3, Cao Chenzhong1,4, Muramatsu Y5, Li Zhiliang1,5   

  1. 1 Institute of Chemistry and Chemical Engineering, ICP, Hunan University, Changsha 410082;
    2 Department of Applied Chemistry, Gnilin Institute of Technology, Guilin 541004;
    3 Department of Applied Physics, Changsha Institute of Technology, Changsha 410073;
    4 Department of Chemistry, Xiangtan Teacher's College, Xiangtan 411100;
    5 Department of Chemistry and Biochemistry, Waseda University, Tokyo 178, Japan
  • Received:1997-05-09 Revised:1997-06-19 Published:1997-10-05 Online:2018-01-22

Abstract: Systematic studies were made on the 13C NMR and its regularity of chemical shift sum (CSS).In this paper, a set of novel molecular graph theoretical parameters, called the distance-edge vector (λ), was developed and found to be excellently correlated to 13C NMR CSS of alkanes. The modified backpropagation (MBP) naural networks were also applied to estimate and predict, the ressults satisfactoryly.

Key words: 13C NMR, CSS, Novel distance-edge vector (λ), Alkanes, Neural networks, BMP