Experimental evaluation and artificial neural network modeling of thermal conductivity of water based nanofluid containing magnetic copper nanoparticles

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2019.124127 ◽

2020 ◽

Vol 551 ◽

pp. 124127 ◽

Cited By ~ 9

Author(s):

Mahyar Ghazvini ◽

Heydar Maddah ◽

Reza Peymanfar ◽

Mohammad Hossein Ahmadi ◽

Ravinder Kumar

Keyword(s):

Neural Network ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Copper Nanoparticles ◽

Experimental Evaluation ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Water Based ◽

Artificial Neural

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Artificial Neural Network Modeling of Grinding of Ductile Cast Iron using Water Based SiO2 Nanocoolant

International Journal of Automotive and Mechanical Engineering ◽

10.15282/ijame.9.2013.15.0137 ◽

2014 ◽

Vol 9 ◽

pp. 1649-1661 ◽

Cited By ~ 4

Author(s):

M.M. Rahman ◽

K. Kadirgama ◽

Azma Salwani Ab Aziz

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Cast Iron ◽

Network Modeling ◽

Ductile Cast Iron ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Water Based ◽

Artificial Neural

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Stability, thermal performance and artificial neural network modeling of viscosity and thermal conductivity of Al2O3-ethylene glycol nanofluids

Powder Technology ◽

10.1016/j.powtec.2020.01.006 ◽

2020 ◽

Vol 363 ◽

pp. 360-368 ◽

Cited By ~ 6

Author(s):

Long Li ◽

Yuling Zhai ◽

Yajuan Jin ◽

Jiang Wang ◽

Hua Wang ◽

...

Keyword(s):

Neural Network ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Ethylene Glycol ◽

Thermal Performance ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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Experimental Evaluation of Mathematical and Artificial Neural Network Modeling of Energy Storage System

Dynamical Systems in Applications - Springer Proceedings in Mathematics & Statistics ◽

10.1007/978-3-319-96601-4_5 ◽

2018 ◽

pp. 49-62 ◽

Cited By ~ 5

Author(s):

Adrian Chmielewski ◽

Jakub Możaryn ◽

Robert Gumiński ◽

Krzysztof Bogdziński ◽

Przemysław Szulim

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Energy Storage ◽

Experimental Evaluation ◽

Network Modeling ◽

Storage System ◽

Energy Storage System ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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A Novel Correlation to Calculate Thermal Conductivity of Aqueous Hybrid Graphene Oxide/Silicon Dioxide Nanofluid: Synthesis, Characterizations, Preparation, and Artificial Neural Network Modeling

Arabian Journal for Science and Engineering ◽

10.1007/s13369-020-04885-w ◽

2020 ◽

Vol 45 (11) ◽

pp. 9747-9758 ◽

Cited By ~ 3

Author(s):

Quyen Nguyen ◽

Reza Rizvandi ◽

Arash Karimipour ◽

Omid Malekahmadi ◽

Quang-Vu Bach

Keyword(s):

Neural Network ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Graphene Oxide ◽

Silicon Dioxide ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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A co-training style semi-supervised artificial neural network modeling and its application in thermal conductivity prediction of polymeric composites filled with BN sheets

Energy and AI ◽

10.1016/j.egyai.2021.100052 ◽

2021 ◽

Vol 4 ◽

pp. 100052

Author(s):

Yunmin Liang ◽

Zhichun Liu ◽

Wei Liu

Keyword(s):

Neural Network ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Network Modeling ◽

Polymeric Composites ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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Artificial Neural Network Modeling of Liquid Thermal Conductivity for alkanes, ketones and silanes

Journal of Physics Conference Series ◽

10.1088/1742-6596/923/1/012054 ◽

2017 ◽

Vol 923 ◽

pp. 012054 ◽

Cited By ~ 2

Author(s):

G Latini ◽

G Di Nicola ◽

M Pierantozzi ◽

G Coccia ◽

S Tomassetti

Keyword(s):

Neural Network ◽

Thermal Conductivity ◽

Artificial Neural Network ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural ◽

Liquid Thermal Conductivity

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Artificial Neural Network Modeling of Pavement Performance using Expert Judgement

Road Materials and Pavement Design ◽

10.3166/rmpd.3.373-384 ◽

2002 ◽

Vol 3 (4) ◽

pp. 373-384

Author(s):

Medhi Parvani

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Modeling ◽

Pavement Performance ◽

Expert Judgement ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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Artificial Neural Network Modeling of Phytoestrogen Binding to Estrogen Receptors

Letters in Drug Design & Discovery ◽

10.2174/157018006778194871 ◽

2006 ◽

Vol 3 (7) ◽

pp. 436-442 ◽

Cited By ~ 4

Author(s):

S. Agatonovic-Kustrin ◽

J. Turner

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Estrogen Receptors ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural

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An Artificial Neural Network Modeling to Study Unpredictable Degradation of Carbon Steel Marine Structure with Environmental Variables: Chloride, Sulphate, Bicarbonates, pH

Innovations in Corrosion and Materials Science (Formerly Recent Patents on Corrosion Science) ◽

10.2174/2352094904999141202103233 ◽

2015 ◽

Vol 4 (2) ◽

pp. 127-133

Author(s):

Subir Paul ◽

Sujit K Guchhait ◽

Kamal Goswami

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Carbon Steel ◽

Environmental Variables ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Marine Structure ◽

Artificial Neural

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Porosity Estimation of Mesoporous TiO 2 ‐ZnO Nanocrystalline by Artificial Neural Network Modeling

Chemical Engineering & Technology ◽

10.1002/ceat.202000297 ◽

2021 ◽

Author(s):

Soroush Soltani ◽

Taha Roodbar Shojaei ◽

Nasrin Khanian ◽

Thomas Shean Yaw Choong ◽

Nilofar Asim ◽

...

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Modeling ◽

Neural Network Modeling ◽

Artificial Neural Network Modeling ◽

Artificial Neural ◽

Porosity Estimation

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