物理化学学报 >> 2000, Vol. 16 >> Issue (09): 844-849.doi: 10.3866/PKU.WHXB20000916

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氢键碱度的神经网络法计算

傅旭春, 俞庆森, 梁文权   

  1. 浙江大学药学院,杭州 310031|浙江大学理学院化学系,杭州 310027
  • 收稿日期:1999-11-26 修回日期:2000-03-09 发布日期:2000-09-15
  • 通讯作者: 傅旭春

Calculation of Hydrogen-Bond Basicity by Artificial Neural Network Method

Fu Xu-Chun, Yu Qing-Sen, Liang Wen-Quan   

  1. School of Pharmacy,Zhejiang University,Hangzhou 310031|Department of Chemistry,School of Sclence,Zhejiang University,Hangzhou 310027
  • Received:1999-11-26 Revised:2000-03-09 Published:2000-09-15
  • Contact: Fu Xu-Chun

关键词: 氢键, 氢键碱度, AMl法, 量子化学参数, BP神经网络

Abstract:

The artificial neural network method is utilized to study the correlation between the overall hydrogen- bond basicity (Σβ2H ) values of 231 diverse compounds and their quantum chemical parameters. There are nonlinear relationships of theΣβ2H values with the quantum chemical parameters. The BP neural networks can predict theΣβ2H values when the neural units of the input layers are the quantum chemical parameters. The structures of the BP neural networks or the quantum chemical parameters are different when the compounds belong to different classes.

Key words: Hydrogen-bond, Hydrogen-bond basicity, AMl method, Quantum chemical parameters, BP neural network