CORRELATION BETWEEN STRUCTURE AND NORMAL BOILING POINTS OF HALOALKANES C-1-C-4 USING NEURAL NETWORKS
被引:53
作者:
BALABAN, AT
论文数: 0引用数: 0
h-index: 0
机构:UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811
BALABAN, AT
BASAK, SC
论文数: 0引用数: 0
h-index: 0
机构:UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811
BASAK, SC
COLBURN, T
论文数: 0引用数: 0
h-index: 0
机构:UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811
COLBURN, T
GRUNWALD, GD
论文数: 0引用数: 0
h-index: 0
机构:UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811
GRUNWALD, GD
机构:
[1] UNIV MINNESOTA,NAT RESOURCES RES INST,DULUTH,MN 55811
[2] UNIV MINNESOTA,DEPT COMP SCI,DULUTH,MN 55812
来源:
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
|
1994年
/
34卷
/
05期
关键词:
D O I:
10.1021/ci00021a016
中图分类号:
O6 [化学];
学科分类号:
0703 ;
摘要:
By using neural networks, correlations were established between chemical structure and boiling points of chlorofluorocarbons with 1, 1-2, or 1-4 carbon atoms (15, 62, and 276 compounds, respectively) as well as of halomethanes with up to four different halogens (48 compounds). The molecular descriptors included the number of carbon atoms and of each type of halogen atom as well as topological indices. Results were validated by the jackknifing procedure. The correlation coefficients were r = 0.985-0.995. Predictions were made for the boiling points of several haloethanes.