DocumentCode :
2351752
Title :
Artificial neural networks applied to theoretical chemistry
Author :
de Almeida, M.B. ; Belchior, J.C. ; Braga, J.P. ; Braga, A.P.
Author_Institution :
Dept. de Engenharia Eletronica, Univ. Fed. de Minas Gerais, Belo Horizonte, Brazil
fYear :
1998
fDate :
9-11 Dec 1998
Firstpage :
232
Lastpage :
234
Abstract :
Artificial neural networks are used to invert the potential energy function for diatomic molecules. The latter was based on radial basis function technique. Fifteen diatomic systems were used and leave-three-out for testing the learning procedure. The relative average error of the inverted potential compared against the exact one is about 5% which is considered to be satisfactory
Keywords :
DIM calculations; chemistry computing; neural nets; potential energy functions; chemistry; diatomic molecules; neural networks; potential energy function inversion; radial basis function technique; Artificial neural networks; Chemistry; Cost function; Equations; Neural networks; Particle scattering; Performance evaluation; Potential energy; Quantum mechanics; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1998. Proceedings. Vth Brazilian Symposium on
Conference_Location :
Belo Horizonte
Print_ISBN :
0-8186-8629-4
Type :
conf
DOI :
10.1109/SBRN.1998.731036
Filename :
731036
Link To Document :
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