ISSN:
0192-8651
Keywords:
Computational Chemistry and Molecular Modeling
;
Biochemistry
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
,
Computer Science
Notes:
An artificial neural network (ANN) method for the prediction of force constants of chemical bonds in large, polyatomic molecules was developed. The force constant information evaluated is to be used for generating accurate estimates of the Hessian used in Newton-Raphson-type ab initio molecular structure optimization schemes. Different network topologies as well as a training procedure based on simulated annealing are evaluated. The results show that an ANN can be designed and trained to provide force constant information within a 1.5 to 5% error band even if the range of the force constants evaluated is very large (from triple bonds to hydrogen bridges). © 1995 by John Wiley & Sons, Inc.
Additional Material:
7 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/jcc.540160802
