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@article{485230,
author = {Havel, Josef and Lubal, Přemysl and Farková, Marta},
article_location = {OXFORD},
article_number = {14-15},
keywords = {artificial neural networks; chemical equilibria},
language = {eng},
issn = {0277-5387},
journal = {POLYHEDRON},
title = {Evaluation of chemical equilibria with the use of artificial neural networks},
volume = {21},
year = {2002}
}
TY - JOUR
ID - 485230
AU - Havel, Josef - Lubal, Přemysl - Farková, Marta
PY - 2002
TI - Evaluation of chemical equilibria with the use of artificial neural networks
JF - POLYHEDRON
VL - 21
IS - 14-15
SP - 1375-1384
EP - 1375-1384
PB - PERGAMON-ELSEVIER SCIENCE LTD
SN - 02775387
KW - artificial neural networks
KW - chemical equilibria
N2 - Multivariate calibration with experimental design (ED) and artificial neural networks (ANN) modeling can be used to estimate equilibria constants from any kind of protonation or metal-ligand equilibrium data like potentiometry, polarography, spectrophotometry, extraction, etc. The method was tested on evenly or randomly distributed experimental error-free data and data with random noise and the results show that even rather higher experimental errors do not influence significantly the prediction power and correctness of ANN prediction. ANN with appropriate ED can provide accurate prediction of stability constants with the relative errors in the range of +/-4% or smaller while the approach is very robust. Comparison with a hard model evaluation based on non-linear regression techniques shows excellent agreement. Proposed ANN method is of a general nature and, in principal, can be adopted to any analytical technique used in equilibria studies. (C) 2002 Elsevier Science Ltd. All rights reserved.
ER -
HAVEL, Josef, Přemysl LUBAL a Marta FARKOVÁ. Evaluation of chemical equilibria with the use of artificial neural networks. \textit{POLYHEDRON}. OXFORD: PERGAMON-ELSEVIER SCIENCE LTD, 2002, roč.~21, 14-15, s.~1375-1384. ISSN~0277-5387.
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