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Thermodynamic data for cryogenic carbon dioxide capture from natural gas: A review
The increasing global energy demand has compelled the researchers to utilize the
undeveloped contaminated natural gas (NG) reservoirs. However, due to the emissions …
undeveloped contaminated natural gas (NG) reservoirs. However, due to the emissions …
Modeling of Soret and Dufour's convective heat transfer in nanofluid flow through a moving needle with artificial neural network
In this study, forced convective heat and mass transfer of a nanofluid using the Buongiorno
model and moving radially through a thin needle has been analyzed using the Runge–Kutta …
model and moving radially through a thin needle has been analyzed using the Runge–Kutta …
A review on process modeling and simulation of cryogenic carbon capture for post-combustion treatment
The cryogenic carbon capture (CCC) process is a promising post-combustion CO2 removal
method. This method is very novel compared with conventional and well-developed …
method. This method is very novel compared with conventional and well-developed …
Short-, medium-, and long-term prediction of carbon dioxide emissions using wavelet-enhanced extreme learning machine
Carbon dioxide (CO2) is the main greenhouse gas responsible for global warming. Early
prediction of CO2 is critical for develo** strategies to mitigate the effects of climate …
prediction of CO2 is critical for develo** strategies to mitigate the effects of climate …
Modeling of Darcy–Forchheimer bioconvective Powell Eyring nanofluid with artificial neural network
Nano-engineering has recently grown to include the usages of nanoparticles in combination
with base fluids to improve the thermal properties of pure fluids. Today's industry focuses …
with base fluids to improve the thermal properties of pure fluids. Today's industry focuses …
Significance of EMHD graphene oxide (GO) water ethylene glycol nanofluid flow in a Darcy–Forchheimer medium by machine learning algorithm
The low heat efficiency of base fluids is a key problem among investigators. To address this
issue, investigators utilize tiny-sized (1–100 nm) metal solid material inside the base fluids to …
issue, investigators utilize tiny-sized (1–100 nm) metal solid material inside the base fluids to …
[HTML][HTML] Comparative study of artificial neural network versus parametric method in COVID-19 data analysis
Since the previous two years, a new coronavirus (COVID-19) has found a major global
problem. The speedy pathogen over the globe was followed by a shockingly large number …
problem. The speedy pathogen over the globe was followed by a shockingly large number …
Significance of bioconvective flow of MHD thixotropic nanofluid passing through a vertical surface by machine learning algorithm
Scientists have made significant contributions in the current decade due to the importance of
bioconvection in biotechnology and a variety of biological systems. In this study, a …
bioconvection in biotechnology and a variety of biological systems. In this study, a …
Optimization of Darcy-Forchheimer squeezing flow in nonlinear stratified fluid under convective conditions with artificial neural network
In cases when high velocity occurs, non-Darcy phenomena are essential for explaining fluid
motion in porous media and have wide range of applications. The present study displays the …
motion in porous media and have wide range of applications. The present study displays the …
[HTML][HTML] Modeling and survival exploration of breast carcinoma: a statistical, maximum likelihood estimation, and artificial neural network perspective
The core objective of this research is to describe the behavior of the distribution using the
MLE method to estimate its parameters, as well as to determine the optimal Artificial Neural …
MLE method to estimate its parameters, as well as to determine the optimal Artificial Neural …