Machine learning for design principles for single atom catalysts towards electrochemical reactions
Machine learning (ML) integrated density functional theory (DFT) calculations have recently
been used to accelerate the design and discovery of heterogeneous catalysts such as single …
been used to accelerate the design and discovery of heterogeneous catalysts such as single …
Prospects and challenges of the machine learning and data-driven methods for the predictive analysis of power systems: A review
W Strielkowski, A Vlasov, K Selivanov, K Muraviev… - Energies, 2023 - mdpi.com
The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …
systems offers the potential to accurately predict and manage the behavior of these systems …
[HTML][HTML] On the prediction of the mechanical properties of ultrafine grain Al-TiO2 nanocomposites using a modified long-short term memory model with beluga whale …
Mechanical properties of fine grain nanocomposites differ from those of conventional
composites due to the in situ effect caused by the addition of nanoparticle reinforcement and …
composites due to the in situ effect caused by the addition of nanoparticle reinforcement and …
Prediction of tribological properties of alumina-coated, silver-reinforced copper nanocomposites using long short-term model combined with golden jackal optimization
In this paper, we present a newly modified machine learning model that employs a long
short-term memory (LSTM) neural network model with the golden jackal optimization (GJO) …
short-term memory (LSTM) neural network model with the golden jackal optimization (GJO) …
[HTML][HTML] An enhanced Dendritic Neural Algorithm to predict the wear behavior of alumina coated silver reinforced copper nanocomposites
Due to the lack of analytical solutions for the wear rates prediction of nanocomposites, we
present a modified machine learning method named Dendritic Neural (DN) to predict the …
present a modified machine learning method named Dendritic Neural (DN) to predict the …
Machine learning to predict biochar and bio-oil yields from co-pyrolysis of biomass and plastics
A Alabdrabalnabi, R Gautam, SM Sarathy - Fuel, 2022 - Elsevier
Because of high oxygen content, pH and viscosity, pyrolysis bio-oil is of low quality.
Upgrading bio-oil can be achieved by co-pyrolysis of biomass with waste plastics, and it is …
Upgrading bio-oil can be achieved by co-pyrolysis of biomass with waste plastics, and it is …
Utilization of Improved Machine Learning Method Based on Artificial Hummingbird Algorithm to Predict the Tribological Behavior of Cu-Al2O3 Nanocomposites …
This paper presents a machine learning model to predict the effect of Al2O3 nanoparticles
content on the wear rates in Cu-Al2O3 nanocomposite prepared using in situ chemical …
content on the wear rates in Cu-Al2O3 nanocomposite prepared using in situ chemical …
Prediction of wear rates of Al-TiO2 nanocomposites using artificial neural network modified with particle swarm optimization algorithm
The prediction of the wear rates and coefficient of friction of composite materials is relatively
complex using mathematical models due to the effect of the manufacturing process on the …
complex using mathematical models due to the effect of the manufacturing process on the …
Comparative evaluation of AI‐based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe3O4‐coated MWCNT hybrid nanofluids for …
Hybrid nanofluids are gaining popularity owing to the synergistic effects of nanoparticles,
which provide them with better heat transfer capabilities than base fluids and normal …
which provide them with better heat transfer capabilities than base fluids and normal …
Precise prediction of performance and emission of a waste derived Biogas–Biodiesel powered Dual–Fuel engine using modern ensemble Boosted regression Tree: A …
P Sharma, BB Sahoo - Fuel, 2022 - Elsevier
The current study looks at using waste-derived biodiesel as pilot fuel and waste-derived
biogas as a gaseous fuel to power a diesel engine in dual-fuel mode. A new ensemble …
biogas as a gaseous fuel to power a diesel engine in dual-fuel mode. A new ensemble …