On the public citation graph

Artificial Neural Networking (ANN) Model for Convective Heat Transfer in Thermally Magnetized Multiple Flow Regimes with Temperature Stratification Effects

0 signed · 76 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ente.201600688openalex-snapshot
Experimental and Neural Network Modeling of Partial Uptake for a Carbon Dioxide/Methane/Water Ternary Mixture on 13X Zeolite
inferredcites →https://doi.org/10.1002/er.5417openalex-snapshot
Experimental study for predicting the specific heat of water based Cu‐Al 2 O 3 hybrid nanofluid using artificial neural network and proposing new correlation
inferredcites →https://doi.org/10.1002/er.5680openalex-snapshot
An experimental study on the comparative analysis of the effect of the number of data on the error rates of artificial neural networks
inferredcites →https://doi.org/10.1002/ghg.1833openalex-snapshot
Application of artificial neural networks (ANN) for vapor‐liquid‐solid equilibrium prediction for CH4‐CO2 binary mixture
inferredcites →https://doi.org/10.1007/s002310100215openalex-snapshot
Heat transfer in stagnation-point flow towards a stretching sheet
inferredcites →https://doi.org/10.1007/s00419-022-02168-4openalex-snapshot
Artificial neural network modeling of MHD slip-flow over a permeable stretching surface
inferredcites →https://doi.org/10.1007/s10973-021-10828-wopenalex-snapshot
Entropy generation of graphene–platinum hybrid nanofluid flow through a wavy cylindrical microchannel solar receiver by using neural networks
inferredcites →https://doi.org/10.1016/j.amc.2004.02.007openalex-snapshot
Numerical study of flow and heat transfer of a non-Newtonian fluid on a rotating porous disk
inferredcites →https://doi.org/10.1016/j.applthermaleng.2015.03.052openalex-snapshot
Heat transfer analysis of a non-Newtonian fluid flowing through a circular tube with twisted tape inserts
inferredcites →https://doi.org/10.1016/j.applthermaleng.2020.115355openalex-snapshot
Heat transfer and power consumption of Newtonian and non-Newtonian liquids in stirred tanks with vertical tube baffles
inferredcites →https://doi.org/10.1016/j.cep.2003.11.007openalex-snapshot
Heat transfer in temperature-dependent non-Newtonian flow
inferredcites →https://doi.org/10.1016/j.cnsns.2008.10.021openalex-snapshot
Effects of partial slip, viscous dissipation and Joule heating on Von Kármán flow and heat transfer of an electrically conducting non-Newtonian fluid
inferredcites →https://doi.org/10.1016/j.csite.2021.101455openalex-snapshot
RANS modeling of turbulent flow and heat transfer of non-Newtonian viscoplastic fluid in a pipe
inferredcites →https://doi.org/10.1016/j.csite.2022.101913openalex-snapshot
A comparative remark on heat transfer in thermally stratified MHD Jeffrey fluid flow with thermal radiations subject to cylindrical/plane surfaces
inferredcites →https://doi.org/10.1016/j.enconman.2010.07.008openalex-snapshot
Heat transfer in pseudo-plastic non-Newtonian fluids with variable thermal conductivity
inferredcites →https://doi.org/10.1016/j.est.2022.103981openalex-snapshot
Prediction of experimental thermal performance of new designed cold plate for electric vehicles’ Li-ion pouch-type battery with artificial neural network
inferredcites →https://doi.org/10.1016/j.euromechflu.2021.12.003openalex-snapshot
The role of Brinkmann ratio on non-Newtonian fluid flow due to a porous shrinking/stretching sheet with heat transfer
inferredcites →https://doi.org/10.1016/j.flowmeasinst.2016.04.003openalex-snapshot
Open channel junction velocity prediction by using a hybrid self-neuron adjustable artificial neural network
inferredcites →https://doi.org/10.1016/j.icheatmasstransfer.2016.03.008openalex-snapshot
Prediction of thermal conductivity of various nanofluids using artificial neural network
inferredcites →https://doi.org/10.1016/j.icheatmasstransfer.2017.02.003openalex-snapshot
A hybrid artificial neural network-genetic algorithm modeling approach for viscosity estimation of graphene nanoplatelets nanofluid using experimental data
inferredcites →https://doi.org/10.1016/j.icheatmasstransfer.2021.105799openalex-snapshot
Computational intelligence of Levenberg-Marquardt backpropagation neural networks to study thermal radiation and Hall effects on boundary layer flow past a stretching sheet
inferredcites →https://doi.org/10.1016/j.icheatmasstransfer.2022.105930openalex-snapshot
Numerical study of pulsatile non-Newtonian blood flow and heat transfer in small vessels under a magnetic field
inferredcites →https://doi.org/10.1016/j.ijheatfluidflow.2007.02.007openalex-snapshot
Numerical study of slip flow heat transfer of non-Newtonian fluids in circular microchannels
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2008.04.010openalex-snapshot
Forced convection of non-Newtonian fluids on a heated flat plate
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2012.10.078openalex-snapshot
Heat transfer coefficients from Newtonian and non-Newtonian fluids flowing in laminar regime in a helical coil
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2021.122203openalex-snapshot
Numerical study on flow, heat transfer and mixing of highly viscous non-newtonian fluid in Sulzer mixer reactor
inferredcites →https://doi.org/10.1016/j.ijthermalsci.2006.02.001openalex-snapshot
Heat transfer in laminar flow of non-Newtonian fluids in ducts of elliptical section
inferredcites →https://doi.org/10.1016/j.ijthermalsci.2022.107624openalex-snapshot
Machine learning approach to predict the heat transfer coefficients pertaining to a radiant cooling system coupled with mixed and forced convection
inferredcites →https://doi.org/10.1016/j.jestch.2019.03.001openalex-snapshot
Numerical design and heat transfer analysis of a non-Newtonian fluid flow for annulus with helical fins
inferredcites →https://doi.org/10.1016/j.molliq.2016.10.049openalex-snapshot
An accurate RBF-NN model for estimation of viscosity of nanofluids
inferredcites →https://doi.org/10.1016/j.molliq.2017.02.015openalex-snapshot
An inspection of thermal conductivity of CuO-SWCNTs hybrid nanofluid versus temperature and concentration using experimental data, ANN modeling and new correlation
inferredcites →https://doi.org/10.1016/j.molliq.2019.112307openalex-snapshot
The thermal conductivity, viscosity, and cloud points of bentonite nanofluids with n-pentadecane as the base fluid
inferredcites →https://doi.org/10.1016/j.petrol.2011.03.002openalex-snapshot
Automatic recognition of oil reservoir models from well testing data by using multi-layer perceptron networks
inferredcites →https://doi.org/10.1016/j.physe.2016.08.020openalex-snapshot
Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks
inferredcites →https://doi.org/10.1016/j.powtec.2012.04.045openalex-snapshot
Modeling the influence of a process control agent on the properties of metal matrix composite powders using artificial neural networks
inferredcites →https://doi.org/10.1016/j.powtec.2014.06.062openalex-snapshot
Artificial neural network approach for prediction of thermal behavior of nanofluids flowing through circular tubes
inferredcites →https://doi.org/10.1016/j.powtec.2019.05.034openalex-snapshot
Artificial intelligence in the field of nanofluids: A review on applications and potential future directions
inferredcites →https://doi.org/10.1016/j.powtec.2019.07.086openalex-snapshot
Developing dissimilar artificial neural networks (ANNs) to prediction the thermal conductivity of MWCNT-TiO2/Water-ethylene glycol hybrid nanofluid
inferredcites →https://doi.org/10.1016/j.proeng.2017.09.845openalex-snapshot
Study on Heat Transfer of Non-Newtonian Power Law Fluid in Pipes with Different Cross Sections
inferredcites →https://doi.org/10.1016/j.spmi.2021.106864openalex-snapshot
Artificial intelligence approach on predicting current values of polymer interface Schottky diode based on temperature and voltage: An experimental study
inferredcites →https://doi.org/10.1016/s0017-9310(03)00029-2openalex-snapshot
Unsteady flow of a non-Newtonian fluid above a rotating disk with heat transfer
inferredcites →https://doi.org/10.1016/s0017-9310(98)00202-6openalex-snapshot
An experimental study of heat transfer by laminar natural convection between an electrically-heated vertical plate and both Newtonian and non-Newtonian fluids
inferredcites →https://doi.org/10.1016/s0142-727x(00)00063-1openalex-snapshot
Heat transfer to non-Newtonian flows over a cylinder in cross flow
inferredcites →https://doi.org/10.1016/s0735-1933(01)00242-1openalex-snapshot
Effect of viscosity models on the stability of a Non-Newtonian fluid in a channel with heat transfer
inferredcites →https://doi.org/10.1016/s0960-0779(01)00066-2openalex-snapshot
Heat and mass transfer in hydromagnetic flow of the non-Newtonian fluid with heat source over an accelerating surface through a porous medium
inferredcites →https://doi.org/10.1615/heattransres.2021039444openalex-snapshot
A COMPREHENSIVE AND COMPARATIVE EXPERIMENTAL ANALYSIS ON THERMAL CONDUCTIVITY OF TiO2-CaCO3/WATER HYBRID NANOFLUID: PROPOSING NEW CORRELATION AND ARTIFICIAL NEURAL NETWORK OPTIMIZATION

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4638637openalex-extracted
Intelligent Neural Computing to Investigate the Heat and Mass Transmission in Nanofluidic System between Two Rotating Permeable Disks
inferred← citeshttps://doi.org/10.1002/htj.22844openalex-snapshot
Variable thermal conductivity influence on micropolar nanofluid flow triggered by a stretchable disk with Arrhenius activation energy
inferred← citeshttps://doi.org/10.1007/s00231-026-03648-xopenalex-snapshot
Experimental investigation and hybrid AI-Based optimization of laminar convective heat transfer between stationary parallel disks
inferred← citeshttps://doi.org/10.1007/s10973-026-15365-yopenalex-snapshot
Numerical investigation of heat transfer in Williamson nanofluid flow with the Cattaneo–Christov double diffusion model using an artificial neural network approach
inferred← citeshttps://doi.org/10.1007/s12668-024-01437-6openalex-snapshot
Computational Analysis to Explore Bioconvective Williamson Nanofluid Non-Darcian Flow over a Convective Cylindrical Surface with Gyrotactic Microorganisms and Activation Energy Aspects
inferred← citeshttps://doi.org/10.1007/s41939-026-01187-wopenalex-snapshot
Artificial intelligence neural network (AINN) with levenberg–marquardt training algorithm for heat and mass transport exploration of Ag-CuO/water hybrid nanofluid
inferred← citeshttps://doi.org/10.1016/b978-0-443-21574-2.00003-4openalex-snapshot
Application of artificial intelligence techniques for heat exchanger predictions in food industry
inferred← citeshttps://doi.org/10.1016/j.applthermaleng.2025.125763openalex-snapshot
Prediction of supercritical CO2 flow and heat transfer behaviors in zigzag-type printed circuit heat exchangers by improved POD-GABP reduced order model
inferred← citeshttps://doi.org/10.1016/j.csite.2024.104099openalex-snapshot
Group theoretic thermal analysis on heat transfer coefficient (HTC) at thermally slip surface with tangent hyperbolic fluid: AI based decisions
inferred← citeshttps://doi.org/10.1016/j.csite.2025.107067openalex-snapshot
Neural and neuro-fuzzy simulation of mixed convective Carreau blood nanofluid flow with magnesium oxide nanoparticles
inferred← citeshttps://doi.org/10.1016/j.dynatmoce.2026.101670openalex-snapshot
Dynamic interaction of lorentz forces and arrhenius thermal kinetics in shear-thinning/thickening fluids through porous medium
inferred← citeshttps://doi.org/10.1016/j.enganabound.2025.106411openalex-snapshot
Improved semi-analytical modeling for heat conduction and thermal stress in heterogeneous semi-infinite media
inferred← citeshttps://doi.org/10.1016/j.icheatmasstransfer.2026.110969openalex-snapshot
Tensor flow based neural network modeling of microbial bioconvection over porous surfaces under Coriolis effects using Cattaneo-Christov heat and mass flux
inferred← citeshttps://doi.org/10.1016/j.icheatmasstransfer.2026.112474openalex-snapshot
Prediction of heat transfer for film boiling on a vertical flat plate for a wide parametric condition using artificial neural network
inferred← citeshttps://doi.org/10.1016/j.rineng.2024.103829openalex-snapshot
Artificial intelligence and numerical simulation based assessment of trihybrid structured flow over a curved geometry: Thermalized case analysis
inferred← citeshttps://doi.org/10.1016/j.tca.2026.180299openalex-snapshot
Optimizing micropolar nanofluid flow predictions using the Levenberg–Marquardt Algorithm
inferred← citeshttps://doi.org/10.1080/01430750.2023.2196988openalex-snapshot
Galerkin finite element analysis of heat and mass transfer of Jeffrey, Maxwell and Oldroyd-B nanofluids in a vertical annulus with an induced magnetic field and a non–uniform heat source/sink
inferred← citeshttps://doi.org/10.1088/2631-8695/ae698aopenalex-snapshot
Hybrid PINN–RBF framework with ɛ -weighted Robin correction for singularly perturbed delay parabolic convection–diffusion equations
inferred← citeshttps://doi.org/10.1177/09544062251337600openalex-snapshot
A comparative performance analysis of machine learning techniques for optimizing heat transfer between parallel disks
inferred← citeshttps://doi.org/10.1615/jpormedia.2024053402openalex-snapshot
ADVANCED NEURAL COMPUTING FRAMEWORK FOR PREDICTING FLOW ATTRIBUTES OF NONSTANDARD NANOFLUIDS INCORPORATING MULTIPLE NOVEL PHYSICAL PARAMETERS
inferred← citeshttps://doi.org/10.2139/ssrn.6826559openalex-snapshot
Prediction of heat transfer for film boiling of water on a vertical flat plate for a wide parametric condition using Artificial Neural Network
inferred← citeshttps://doi.org/10.28991/cej-2023-09-09-04openalex-snapshot
An Intelligent Approach for Predicting Mechanical Properties of High-Volume Fly Ash (HVFA) Concrete
inferred← citeshttps://doi.org/10.3389/fsufs.2024.1344370openalex-snapshot
Dairy factory milk product processing and sustainable of the shelf-life extension with artificial intelligence: a model study
inferred← citeshttps://doi.org/10.3390/buildings12122093openalex-snapshot
Prediction of Blast-Induced Structural Response and Associated Damage Using Machine Learning
inferred← citeshttps://doi.org/10.3390/engproc2026122010openalex-snapshot
Artificial Neural Network Model for Predicting the Characteristics of a Solar Vacuum Tube System for Domestic Hot Water Heating
inferred← citeshttps://doi.org/10.3390/math10183228openalex-snapshot
Neural Network-Based Modeling for Risk Evaluation and Early Warning for Large-Scale Sports Events
inferred← citeshttps://doi.org/10.3390/math11020326openalex-snapshot
Computational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networking
inferred← citeshttps://doi.org/10.3390/sym17081347openalex-snapshot
Numerical–ANN Framework for Thermal Analysis of MHD Water-Based Prandtl Nanofluid Flow over a Stretching Sheet Using Bvp4c
inferred← citeshttps://doi.org/10.3390/w18131568openalex-snapshot
Artificial Neural Network and Support Vector Regression for Predicting Turbulent Bursting in Bluff-Body Hydrodynamics
inferred← citeshttps://doi.org/10.37394/232013.2024.19.14openalex-snapshot
Influence of Chemical and Radiation on an Unsteady MHD Oscillatory Flow using Artificial Neural Network (ANN)
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.