About: Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes

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About: Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes Goto Sponge NotDistinct Permalink

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	A use of artificial neural networks (ANN) and various experimental designs (ED) for refinement of experimental data obtained in a polarographic metal-ligand equilibrium study of fully dynamic (labile) metal complexes was thoroughly examined. ANN were tested on evenly and randomly distributed experimental error-free and error-corrupted data. It was found that randomly distributed experimental data did not influence the prediction power of ANN. Numerous tests demonstrated that ANN with appropriate ED can provide accurate prediction in the stability constants with the absolute errors in the range of +- 0.05 log unit or smaller. ANNs were found exceptionally robust. Random experimental errors have not influence estimates in stability constants much even when errors in pH up to the value of +- 0.1 pH unit were introduced. A special procedure has been worked out that allows to minimise the influence of error-corrupted data even further; no significant difference was observed between results obtained on erro A use of artificial neural networks (ANN) and various experimental designs (ED) for refinement of experimental data obtained in a polarographic metal-ligand equilibrium study of fully dynamic (labile) metal complexes was thoroughly examined. ANN were tested on evenly and randomly distributed experimental error-free and error-corrupted data. It was found that randomly distributed experimental data did not influence the prediction power of ANN. Numerous tests demonstrated that ANN with appropriate ED can provide accurate prediction in the stability constants with the absolute errors in the range of +- 0.05 log unit or smaller. ANNs were found exceptionally robust. Random experimental errors have not influence estimates in stability constants much even when errors in pH up to the value of +- 0.1 pH unit were introduced. A special procedure has been worked out that allows to minimise the influence of error-corrupted data even further; no significant difference was observed between results obtained on erro (en)
Title	Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes (en)
skos:prefLabel	Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes Evaluation of Equilibria with Use of Artificial Neural Networks (ANN). II. ANN and Experimental Design as a Tool in Electrochemical Data Evaluation for Fully Dynamic (Labile) Metal Complexes (en)
skos:notation	RIV/00216224:14310/01:00004475!RIV/2002/MSM/143102/N
http://linked.open.../vavai/riv/strany	295
http://linked.open...avai/riv/aktivita	Z
http://linked.open...avai/riv/aktivity	Z(MSM 143100011)
http://linked.open...iv/cisloPeriodika	4
http://linked.open...vai/riv/dodaniDat	2002
http://linked.open...aciTvurceVysledku	Havel, Josef Farková, Marta
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Přírodovědecká fakulta
http://linked.open...dnocenehoVysledku	679713
http://linked.open...ai/riv/idVysledku	RIV/00216224:14310/01:00004475
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Artificial neural networks / Experimental design / Stability constants / Polarography / Metal complexes / Ion selective electrodes / Metal-ligand equilibria (en)
http://linked.open.../riv/klicoveSlovo	Artificial neural networks / Experimental design / Stability constants / Polarography / Metal complexes / Ion selective electrodes / Metal-ligand equilibria
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[FB061687F110]
http://linked.open...i/riv/nazevZdroje	Electroanalysis
http://linked.open...in/vavai/riv/obor	CG
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...ocetUcastnikuAkce	0 (xsd:int)
http://linked.open...nichUcastnikuAkce	0 (xsd:int)
http://linked.open...UplatneniVysledku	2001
http://linked.open...v/svazekPeriodika	13
http://linked.open...iv/tvurceVysledku	Havel, Josef Farková, Marta Cukrowski, Ignacy
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20143100011
issn	1040-0397
number of pages	14 (xsd:int)
http://localhost/t...ganizacniJednotka	14310

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