NEURAL-NETWORK GRAPH-THEORY APPROACH TO THE PREDICTION OF THE PHYSICAL-PROPERTIES OF ORGANIC-COMPOUNDS

被引：83

作者：

GAKH, AA

GAKH, EG

SUMPTER, BG

NOID, DW

机构：

[1] Chemistry Division, Oak Ridge National Laboratory, Oak Ridge

来源：

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES | 1994年 / 34卷 / 04期

关键词：

D O I：

10.1021/ci00020a017

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

A new computational scheme is developed to predict physical properties of organic compounds on the basis Of their molecular structure. The method uses graph theory to encode the structural information which is the numerical input for a neural network. Calculated results for a series of saturated hydrocarbons demonstrate average accuracies of 1-2% with maximum deviations of 12-14%.

引用

页码：832 / 839

页数：8

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