Multi-objective optimization of nanofluid flow in flat tubes using CFD, Artificial Neural Networks and genetic algorithms

Advanced Powder Technology ◽

10.1016/j.apt.2014.05.014 ◽

2014 ◽

Vol 25 (5) ◽

pp. 1608-1617 ◽

Author(s):

H. Safikhani ◽

A. Abbassi ◽

A. Khalkhali ◽

M. Kalteh

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Multi Objective Optimization ◽

Nanofluid Flow ◽

Multi Objective ◽

Artificial Neural

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CFD modeling and multi-objective optimization of cyclone geometry using desirability function, artificial neural networks and genetic algorithms

Applied Mathematical Modelling ◽

10.1016/j.apm.2012.11.010 ◽

2013 ◽

Vol 37 (8) ◽

pp. 5680-5704 ◽

Author(s):

Khairy Elsayed ◽

Chris Lacor

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Desirability Function ◽

Cfd Modeling ◽

Multi Objective Optimization ◽

Multi Objective ◽

Artificial Neural

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Multi-objective optimization of asymmetric v-shaped ribs in a cooling channel using CFD, artificial neural networks and genetic algorithms

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1007/s40430-016-0698-0 ◽

2016 ◽

Vol 39 (6) ◽

pp. 2319-2329 ◽

Author(s):

Mohammad Darvish Damavandi ◽

Hamed Safikhani ◽

Mojtaba Yahyaabadi

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Cooling Channel ◽

Multi Objective Optimization ◽

Multi Objective ◽

Artificial Neural

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06/00986 Multi-objective optimization of the coal combustion performance with artificial neural networks and genetic algorithms

Fuel and Energy Abstracts ◽

10.1016/s0140-6701(06)80988-4 ◽

2006 ◽

Vol 47 (2) ◽

pp. 142-143

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Coal Combustion ◽

Multi Objective Optimization ◽

Multi Objective ◽

Combustion Performance ◽

Artificial Neural

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Multi-objective optimization of the coal combustion performance with artificial neural networks and genetic algorithms

International Journal of Energy Research ◽

10.1002/er.1070 ◽

2005 ◽

Vol 29 (6) ◽

pp. 499-510 ◽

Author(s):

Hao Zhou ◽

Kefa Cen ◽

Jianren Fan

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Coal Combustion ◽

Multi Objective Optimization ◽

Multi Objective ◽

Combustion Performance ◽

Artificial Neural

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Multi-Objective Optimization Methods Based on Artificial Neural Networks

Search Algorithms and Applications ◽

10.5772/15113 ◽

2011 ◽

Author(s):

Sara Carcangiu ◽

Alessandra Fanni ◽

Augusto Montisci

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Optimization Methods ◽

Multi Objective Optimization ◽

Multi Objective ◽

Artificial Neural

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Application of Multi-Objective optimization algorithm and Artificial Neural Networks at machining process

2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) ◽

10.1109/pria.2013.6528449 ◽

2013 ◽

Author(s):

F. Jafarian ◽

H. Amirabadi ◽

J. Sadri

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Optimization Algorithm ◽

Machining Process ◽

Multi Objective Optimization ◽

Multi Objective ◽

Artificial Neural

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Multi-objective optimization of micro-fin helical coil tubes based on the prediction of artificial neural networks and entropy generation theory

Case Studies in Thermal Engineering ◽

10.1016/j.csite.2021.101676 ◽

2021 ◽

pp. 101676

Author(s):

Jiaming Cao ◽

Xuesheng Wang ◽

Yuyang Yuan ◽

Zhao Zhang ◽

Yanbin Liu

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Entropy Generation ◽

Helical Coil ◽

Multi Objective Optimization ◽

Multi Objective ◽

Generation Theory ◽

Artificial Neural

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Multi-objective optimization of material selection for sustainable products: Artificial neural networks and genetic algorithm approach

Materials & Design (1980-2015) ◽

10.1016/j.matdes.2008.06.006 ◽

2009 ◽

Vol 30 (4) ◽

pp. 1209-1215 ◽

Author(s):

Chang-Chun Zhou ◽

Guo-Fu Yin ◽

Xiao-Bing Hu

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Artificial Neural Networks ◽

Material Selection ◽

Multi Objective Optimization ◽

Multi Objective ◽

Sustainable Products ◽

Genetic Algorithm Approach ◽

Selection For ◽

Artificial Neural

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Investigation on labyrinth spillway multi-objective optimization with an emphasis on predicting discharge coefficient through different artificial neural networks

Measurement ◽

10.1016/j.measurement.2021.109036 ◽

2021 ◽

Vol 174 ◽

pp. 109036 ◽

Author(s):

Ali Mahmoud ◽

Xiaohui Yuan ◽

Taher Hajilounezhad ◽

Yanbin Yuan

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Discharge Coefficient ◽

Multi Objective Optimization ◽

Multi Objective ◽

Artificial Neural

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Implementation of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms for the Multi-Objective Property Prediction and Optimization of Emulsion Polymers

10.15368/theses.2019.82 ◽

2019 ◽

Author(s):

David Chisholm

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Artificial Neural Networks ◽

Property Prediction ◽

Multi Objective ◽

Emulsion Polymers ◽

Artificial Neural ◽

Objective Property

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