Modeling and Optimization of Heterogeneous Photo-Fenton Process with Response Surface Methodology and Artificial Neural Networks

M. B. Kasiri; H. Aleboyeh; A. Aleboyeh

doi:10.1021/es801372q

Modeling and Optimization of Heterogeneous Photo-Fenton Process with Response Surface Methodology and Artificial Neural Networks

Environmental Science & Technology ◽

10.1021/es801372q ◽

2008 ◽

Vol 42 (21) ◽

pp. 7970-7975 ◽

Cited By ~ 144

Author(s):

M. B. Kasiri ◽

H. Aleboyeh ◽

A. Aleboyeh

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Fenton Process ◽

Modeling And Optimization ◽

Artificial Neural

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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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Ultrasound-assisted extraction of polyphenols from avocado residues: Modeling and optimization using response surface methodology and artificial neural networks

Scientia Agropecuaria ◽

10.17268/sci.agropecu.2021.004 ◽

2021 ◽

Vol 12 (1) ◽

pp. 33-40

Author(s):

Lisbeth Monzón ◽

Gabriela Becerra ◽

Elza Aguirre ◽

Gilbert Rodríguez ◽

Eudes Villanueva

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Ultrasound Assisted Extraction ◽

Modeling And Optimization ◽

Assisted Extraction ◽

Ultrasound Assisted ◽

Artificial Neural

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Modeling and optimization II: Comparison of estimation capabilities of response surface methodology with artificial neural networks in a biochemical reaction

Journal of Food Engineering ◽

10.1016/j.jfoodeng.2005.11.025 ◽

2007 ◽

Vol 78 (3) ◽

pp. 846-854 ◽

Cited By ~ 177

Author(s):

Deniz Baş ◽

İsmail H. Boyacı

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Biochemical Reaction ◽

Modeling And Optimization ◽

Artificial Neural

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Modeling and optimization of electrospun PAN nanofiber diameter using response surface methodology and artificial neural networks

Journal of Applied Polymer Science ◽

10.1002/app.36726 ◽

2012 ◽

Vol 126 (1) ◽

pp. 127-135 ◽

Cited By ~ 74

Author(s):

Komeil Nasouri ◽

Hossein Bahrambeygi ◽

Amir Rabbi ◽

Ahmad Mousavi Shoushtari ◽

Ali Kaflou

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Modeling And Optimization ◽

Nanofiber Diameter ◽

Artificial Neural ◽

Pan Nanofiber

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Modeling and optimization of Newfoundland shrimp waste hydrolysis for microbial growth using response surface methodology and artificial neural networks

Marine Pollution Bulletin ◽

10.1016/j.marpolbul.2016.05.075 ◽

2016 ◽

Vol 109 (1) ◽

pp. 245-252 ◽

Cited By ~ 8

Author(s):

Kedong Zhang ◽

Baiyu Zhang ◽

Bing Chen ◽

Liang Jing ◽

Zhiwen Zhu ◽

...

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Response Surface ◽

Microbial Growth ◽

Shrimp Waste ◽

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 ◽

Cited By ~ 33

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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