Enhanced adsorption performance of a novel Fe‐Mn‐Zr metal oxide nanocomposite adsorbent for anionic dyes from binary dye mix: Response surface optimization and neural network modeling

Nahakpam Hitler Singh; Kethonulu Kezo; Animesh Debnath; Biswajit Saha

doi:10.1002/aoc.4165

Enhanced adsorption performance of a novel Fe‐Mn‐Zr metal oxide nanocomposite adsorbent for anionic dyes from binary dye mix: Response surface optimization and neural network modeling

Applied Organometallic Chemistry ◽

10.1002/aoc.4165 ◽

2017 ◽

Vol 32 (3) ◽

pp. e4165 ◽

Cited By ~ 15

Author(s):

Nahakpam Hitler Singh ◽

Kethonulu Kezo ◽

Animesh Debnath ◽

Biswajit Saha

Keyword(s):

Neural Network ◽

Metal Oxide ◽

Response Surface ◽

Network Modeling ◽

Neural Network Modeling ◽

Anionic Dyes ◽

Adsorption Performance ◽

Response Surface Optimization ◽

Enhanced Adsorption ◽

Nanocomposite Adsorbent

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Response surface optimization and artificial neural network modeling of microwave assisted natural dye extraction from pomegranate rind

Industrial Crops and Products ◽

10.1016/j.indcrop.2011.12.032 ◽

2012 ◽

Vol 37 (1) ◽

pp. 408-414 ◽

Cited By ~ 82

Author(s):

Keka Sinha ◽

Papita Das Saha ◽

Siddhartha Datta

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface ◽

Network Modeling ◽

Natural Dye ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Microwave Assisted ◽

Response Surface Optimization ◽

Dye Extraction

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Inspecting the bioenergy potential of noxious Vachellia nilotica weed via pyrolysis: Thermo-kinetic study, neural network modeling and response surface optimization

Renewable Energy ◽

10.1016/j.renene.2021.12.007 ◽

2021 ◽

Author(s):

Abhisek Sahoo ◽

Komal Saini ◽

Shweta Negi ◽

Jitendra Kumar ◽

Kamal K. Pant ◽

...

Keyword(s):

Neural Network ◽

Kinetic Study ◽

Response Surface ◽

Network Modeling ◽

Neural Network Modeling ◽

Response Surface Optimization ◽

Surface Optimization

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Extraction of Epigallocatechin-3-gallate from green tea via supercritical fluid technology: Neural network modeling and response surface optimization

The Journal of Supercritical Fluids ◽

10.1016/j.supflu.2012.12.009 ◽

2013 ◽

Vol 74 ◽

pp. 128-136 ◽

Cited By ~ 52

Author(s):

S.M. Ghoreishi ◽

E. Heidari

Keyword(s):

Neural Network ◽

Response Surface ◽

Supercritical Fluid ◽

Green Tea ◽

Network Modeling ◽

Neural Network Modeling ◽

Response Surface Optimization ◽

Supercritical Fluid Technology ◽

Surface Optimization

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Mixed phase Fe 2 O 3 /Mn 3 O 4 magnetic nanocomposite for enhanced adsorption of methyl orange dye: Neural network modeling and response surface methodology optimization

Applied Organometallic Chemistry ◽

10.1002/aoc.4186 ◽

2017 ◽

Vol 32 (3) ◽

pp. e4186 ◽

Cited By ~ 30

Author(s):

Mahashweta Bhowmik ◽

Krishna Deb ◽

Animesh Debnath ◽

Biswajit Saha

Keyword(s):

Neural Network ◽

Response Surface Methodology ◽

Methyl Orange ◽

Response Surface ◽

Network Modeling ◽

Mixed Phase ◽

Magnetic Nanocomposite ◽

Neural Network Modeling ◽

Methyl Orange Dye ◽

Enhanced Adsorption

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Sonocatalytic Tannery Effluent Degradation –Response Surface Methodology and Particle Swarm Optimization Embedded Artificial Neural Network Modeling Approach

CLEAN - Soil Air Water ◽

10.1002/clen.202100095 ◽

2021 ◽

pp. 2100095

Author(s):

Natarajan Arun Prem Anand ◽

Ramasamy Palani

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Particle Swarm Optimization ◽

Response Surface ◽

Network Modeling ◽

Neural Network Modeling ◽

Tannery Effluent ◽

Swarm Optimization ◽

Artificial Neural Network Modeling

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Reduction of edge effect using response surface methodology and artificial neural network modeling of a spur gear treated by induction with flux concentrators

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-019-03817-9 ◽

2019 ◽

Vol 104 (1-4) ◽

pp. 103-117

Author(s):

Mohamed Khalifa ◽

Noureddine Barka ◽

Jean Brousseau ◽

Philippe Bocher

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Edge Effect ◽

Network Modeling ◽

Spur Gear ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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Artificial Neural Network Modeling of Cutting Force in Turning of Ti-6Al-4V Alloy and Its Comparison with Response Surface Methodology

Advances in Intelligent and Soft Computing - Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011 ◽

10.1007/978-81-322-0491-6_69 ◽

2012 ◽

pp. 761-768 ◽

Cited By ~ 1

Author(s):

Vikas Upadhyay ◽

P. K. Jain ◽

N. K. Mehta

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Cutting Force ◽

Response Surface ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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Comparison of response surface methodology and feedforward neural network modeling for polycaprolactone synthesis using enzymatic polymerization

Biocatalysis and Agricultural Biotechnology ◽

10.1016/j.bcab.2019.101046 ◽

2019 ◽

Vol 18 ◽

pp. 101046 ◽

Cited By ~ 3

Author(s):

Harshini Pakalapati ◽

Senthil Kumar Arumugasamy ◽

Mohammad Khalid

Keyword(s):

Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Network Modeling ◽

Feedforward Neural Network ◽

Enzymatic Polymerization ◽

Neural Network Modeling

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Degradation of ticarcillin by subcritical water oxidation method: Application of response surface methodology and artificial neural network modeling

Journal of Environmental Science and Health Part A ◽

10.1080/10934529.2018.1471023 ◽

2018 ◽

Vol 53 (11) ◽

pp. 975-985 ◽

Cited By ~ 8

Author(s):

Erdal Yabalak

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Water Oxidation ◽

Subcritical Water ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Oxidation Method

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Optimization of supercritical extraction of galegine from Galega officinalis L.: Neural network modeling and experimental optimization via response surface methodology

Korean Journal of Chemical Engineering ◽

10.1007/s11814-016-0304-2 ◽

2016 ◽

Vol 34 (3) ◽

pp. 854-865 ◽

Cited By ~ 7

Author(s):

Pooya Davoodi ◽

Seyyed Mohammad Ghoreishi ◽

Ali Hedayati

Keyword(s):

Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Network Modeling ◽

Supercritical Extraction ◽

Neural Network Modeling ◽

Experimental Optimization ◽

Galega Officinalis

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