An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion

Boti, Vasiliki; Sakkas, Vasilios A.; Albanis, Triantafyllos A.

doi:10.1016/j.chroma.2008.12.070

Cited by 35 publications

(19 citation statements)

References 31 publications

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“…Experimental design was carried out by applying Response Surface Methodology (RSM), widely used for process optimization [36][37][38][39][40][41][42]. This methodology allows optimization of analytical methods by carrying out a relatively small number of experiments and with no prior knowledge of interaction forces between analytes and stationary phase [43][44][45].…”

Section: Data Treatment and Experimental Designmentioning

confidence: 99%

Characterization and optimization by experimental design of a liquid chromatographic method for the separation of hydroxylated polychlorinated biphenyls on a polar-embedded stationary phase

Quintanilla-López

Galindo-Iranzo

Gómara

et al. 2010

Journal of Chromatography A

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Section: Data Treatment and Experimental Designmentioning

confidence: 99%

Characterization and optimization by experimental design of a liquid chromatographic method for the separation of hydroxylated polychlorinated biphenyls on a polar-embedded stationary phase

Quintanilla-López

Galindo-Iranzo

Gómara

et al. 2010

Journal of Chromatography A

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“…On the other hand, ANNs are computational model programs which can approximate complex nonlinear relationships existing between independent (ANN input) and dependent (ANN output) variables to an arbitrary degree of accuracy [37]. These relationships are achieved through learning (or training) of data network.…”

Section: Experimental Design Modeling Optimization By Response Surfmentioning

confidence: 99%

ZnO/Mg-Al Layered Double Hydroxides as a Photocatalytic Bleaching of Methylene Orange - A Black Box Modeling by Artificial Neural Network

Hosseini

Akbari

2016

Bull. Chem. React. Eng. Catal.

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The paper reports the development of ZnO-MgAl layered double hydroxides as an adsorbent-photo catalyst to remove the dye pollutants from aqueous solution and the experiments of a photocatalytic study were designed and modeled by response surface methodology (RSM) and artificial neural network (ANN). The co-precipitation and urea methods were used to synthesize the ZnO-MgAl layered double hydroxides and FT-IR, XRD and SEM analysis were done for characterization of the catalyst.The performance of the ANN model was determined and showed the efficiency of the model in comparison to the RSM method to predict the percentage of dye removal accurately with a determination coefficient (R2) of 0.968. The optimized conditions were obtained as follows: 600 oC, 120 min, 0.05 g and 20 ppm for the calcination temperature, irradiation time, catalyst amount and dye pollutant concentration, respectively. Copyright © 2016 BCREC GROUP. All rights reservedReceived: 22nd January 2016; Revised: 14th March 2016; Accepted:15th March 2016How to Cite: Hosseini, S.A., Akbari, M. (2016). ZnO/Mg-Al Layered Double Hydroxides as a Photocatalytic Bleaching of Methylene Orange - A Black Box Modeling by Artificial Neural Network. Bulletin of Chemical Reaction Engineering & Catalysis, 11 (3): 299-315 (doi: 10.9767/bcrec.11.3.570.299-315)Permalink/DOI: <a href="http://doi.org/10.9767/bcrec.11.3.570.299-315">http://doi.org/10.9767/bcrec.11.3.570.299-315</a>

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“…MSPD presents a reduced consumption of organic solvents, provides high extraction yields and offers a considerable degree of selectivity. MSPD method comprises sample homogenization, cellular disruption, fractionation, and purification in a single process [44]. There are few papers about using MSPD to extract hormones in fatty foods.…”

Section: Introductionmentioning

confidence: 99%

Application of multiwall carbon nanotubes-based matrix solid phase dispersion extraction for determination of hormones in butter by gas chromatography mass spectrometry

Wang

et al. 2011

Journal of Chromatography A

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An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion

Cited by 35 publications

References 31 publications

Characterization and optimization by experimental design of a liquid chromatographic method for the separation of hydroxylated polychlorinated biphenyls on a polar-embedded stationary phase

Characterization and optimization by experimental design of a liquid chromatographic method for the separation of hydroxylated polychlorinated biphenyls on a polar-embedded stationary phase

ZnO/Mg-Al Layered Double Hydroxides as a Photocatalytic Bleaching of Methylene Orange - A Black Box Modeling by Artificial Neural Network

Application of multiwall carbon nanotubes-based matrix solid phase dispersion extraction for determination of hormones in butter by gas chromatography mass spectrometry

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