SIOC English
化学学报
高级检索

化学学报 ›› 2009, Vol. 67 ›› Issue (10): 1109-1115. 上一篇    下一篇

研究论文

芳香胺类化合物N—H键离解能的定量构效关系研究

乔 澍 谢 昆 付 川 祁俊生*

  

  1. (重庆三峡学院化学与环境工程学院 重庆 404000)

  • 投稿日期:2008-10-30 修回日期:2008-12-05 发布日期:2009-05-28
  • 通讯作者: 祁俊生

Quantitative Structure-property Relationship Study on N—H Bond Dissociation Energy of Arylamines

Qiao, Shu Xie, Kun Fu, Chuan Qi, Jun-Sheng*   

  1. (College of Chemistry & Environmental Engineering, Chongqing Three Gorges University, Chongqing 404000)
  • Received:2008-10-30 Revised:2008-12-05 Published:2009-05-28
  • Contact: Qi, Jun-Sheng

PDF

1428

被引次数

1

基于启发式方法(HM)和BP人工神经网络方法建立了5个参数的定量结构性质关系(QSPR)模型, 用于预测80个芳香胺类化合物N—H键的键离解能(BDE). 通过两种方法分别建立了线性和非线性的QSPR模型, 相关系数R分别为0.823和0.976. 通过对模型的稳定性和预测能力进行比较, 发现BP人工神经网络方法能够更好地预测芳香胺类化合物N—H键的BDE值.

关键词: 启发式方法, BP人工神经网络, 定量结构性质关系, 键裂解能

The bond dissociation energy (BDE) of 80 diverse arylamines was modeled using the five descriptors calculated from the molecular structure along with a quantitative structure-property relationship (QSPR) technique. The heuristic method (HM) and back-propagation neural network method were utilized to construct the linear and nonlinear prediction models, leading to the correlation coefficients R of 0.823 and 0.976. By comparison of the stability with prediction ability of the models, it was found that BP network was a good method for predicting the N—H BDE values of arylamines.

Key words: heuristic method, BP artificial neural network, quantitative structure-property relationship (QSPR), bond dissociation energy (BDE)