Application of artificial neural networks for response surface modelling in HPLC method development

Journal of Advanced Research ◽

10.1016/j.jare.2011.04.001 ◽

2012 ◽

Vol 3 (1) ◽

pp. 53-63 ◽

Author(s):

Mohamed A. Korany ◽

Hoda Mahgoub ◽

Ossama T. Fahmy ◽

Hadir M. Maher

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Response Surface ◽

Method Development ◽

Hplc Method ◽

Surface Modelling ◽

Response Surface Modelling ◽

Artificial Neural ◽

Hplc Method Development

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Application of artificial neural networks in HPLC method development

Journal of Pharmaceutical and Biomedical Analysis ◽

10.1016/s0731-7085(97)00170-2 ◽

1998 ◽

Vol 17 (1) ◽

pp. 69-76 ◽

Author(s):

S. Agatonovic-Kustrin ◽

M. Zecevic ◽

L.j. Zivanovic ◽

I.G. Tucker

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Method Development ◽

Hplc Method ◽

Artificial Neural ◽

Hplc Method Development

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Modeling and optimization of pectin extraction from banana peel using artificial neural networks (ANNs) and response surface methodology (RSM)

Journal of Food Measurement & Characterization ◽

10.1007/s11694-021-00852-7 ◽

2021 ◽

Author(s):

Ermias Girma Aklilu

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Banana Peel ◽

Modeling And Optimization ◽

Artificial Neural

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Optimization of hypochlorous acid generation by HCl electrolysis through response surface methodology and artificial neural networks

Journal of Environmental Chemical Engineering ◽

10.1016/j.jece.2021.105826 ◽

2021 ◽

pp. 105826

Author(s):

Muhammad Yaqub ◽

Changyeon Woo ◽

Wontae Lee

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Hypochlorous Acid ◽

Acid Generation ◽

Artificial Neural

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Simultaneous extraction of polysaccharides and polyphenols from blackcurrant fruits: Comparison between response surface methodology and artificial neural networks

Industrial Crops and Products ◽

10.1016/j.indcrop.2021.113682 ◽

2021 ◽

Vol 170 ◽

pp. 113682

Author(s):

Xueying Bu ◽

Yaqin Xu ◽

Meimei Zhao ◽

Dalong Li ◽

Jiaheng Zou ◽

...

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Simultaneous Extraction ◽

Artificial Neural

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Comparative assessment of response surface methodology and artificial neural networks in forecasting biodiesel yield from waste cooking sunflower oil

Materials Today Proceedings ◽

10.1016/j.matpr.2021.02.291 ◽

2021 ◽

Author(s):

B. Devaraj Naik ◽

M. Udayakumar

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Sunflower Oil ◽

Comparative Assessment ◽

Artificial Neural

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Photocatalytic oxidation of treated municipal wastewaters for the removal of phenolic compounds: optimization and modeling using response surface methodology (RSM) and artificial neural networks (ANNs)

Journal of Chemical Technology & Biotechnology ◽

10.1002/jctb.3755 ◽

2012 ◽

Vol 87 (10) ◽

pp. 1385-1395 ◽

Author(s):

Maria Antonopoulou ◽

Vassilios Papadopoulos ◽

Ioannis Konstantinou

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Phenolic Compounds ◽

Response Surface ◽

Photocatalytic Oxidation ◽

Artificial Neural ◽

Municipal Wastewaters

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Optimizing Wear Behavior of Epoxy Composites Using Response Surface Methodology and Artificial Neural Networks

Polymer Composites ◽

10.1002/pc.25089 ◽

2018 ◽

Vol 40 (7) ◽

pp. 2812-2818

Author(s):

D. Satish Kumar ◽

M. Rajmohan

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Wear Behavior ◽

Epoxy Composites ◽

Artificial Neural

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Modeling the Performance of Vortex Tube using Response Surface Methodology and Artificial Neural Networks

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/390/1/012010 ◽

2018 ◽

Vol 390 ◽

pp. 012010 ◽

Author(s):

G Suresh Kumar ◽

B Veerabhadra Reddy ◽

G Sankaraiah ◽

P Venkateshwar Reddy

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Vortex Tube ◽

Artificial Neural

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Enhanced removal of Cr(VI) by cerium oxide polyaniline composite: Optimization and modeling approach using response surface methodology and artificial neural networks

Journal of Environmental Chemical Engineering ◽

10.1016/j.jece.2015.03.028 ◽

2015 ◽

Vol 3 (2) ◽

pp. 870-885 ◽

Author(s):

S. Mandal ◽

S.S. Mahapatra ◽

R.K. Patel

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Cerium Oxide ◽

Composite Optimization ◽

Modeling Approach ◽

Artificial Neural

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Modeling the calcium and magnesium removal from seawater by immobilized biomass of ureolytic bacteria Bacillus subtilis through response surface methodology and artificial neural networks

10.5004/dwt.2018.22665 ◽

2018 ◽

Vol 118 ◽

pp. 294-303 ◽

Author(s):

Dayana Arias ◽

Mariella Rivas ◽

Ricardo Guiñez ◽

Luis A. Cisternas

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Bacillus Subtilis ◽

Artificial Neural Networks ◽

Response Surface ◽

Immobilized Biomass ◽

Calcium And Magnesium ◽

Artificial Neural ◽

Magnesium Removal ◽

Ureolytic Bacteria

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