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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

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

Download Full-text

Comparison of Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) Modeling Approaches in Predicting the Deposition Efficiency of Plasma Sprayed Alumina Coatings on AZ31B Magnesium Alloy

Journal of Advanced Microscopy Research ◽

10.1166/jamr.2017.1317 ◽

2017 ◽

Vol 12 (1) ◽

pp. 40-49 ◽

Author(s):

D. Thirumalaikumarasamy ◽

V. Balasubramanian ◽

S. Sree Sabari ◽

S. Vignesh

Keyword(s):

Neural Networks ◽

Response Surface Methodology ◽

Artificial Neural Networks ◽

Magnesium Alloy ◽

Response Surface ◽

Deposition Efficiency ◽

Alumina Coatings ◽

Az31b Magnesium Alloy ◽

Artificial Neural ◽

Download Full-text

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

Download Full-text