Application of meta-heuristic algorithms for training neural networks and deep learning architectures: A comprehensive review
M Kaveh, MS Mesgari - Neural Processing Letters, 2023 - Springer
The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …
and deep learning (DL) architectures is considered one of the most challenging machine …
Recent advances in artificial neural network research for modeling hydrogen production processes
Abstract Artificial Neural Networks (ANN) have been widely used by scientists in a variety of
energy modes (biomass, wind, solar, geothermal, and hydroelectric). This review highlights …
energy modes (biomass, wind, solar, geothermal, and hydroelectric). This review highlights …
Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture
LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
Weighted random k satisfiability for k= 1, 2 (r2SAT) in discrete Hopfield neural network
Current studies on non-systematic satisfiability in Discrete Hopfield Neural Network are able
to avoid production of repetitive final neuron states which improves the quality of global …
to avoid production of repetitive final neuron states which improves the quality of global …
Exploring the intersection of artificial intelligence and clinical healthcare: a multidisciplinary review
Artificial intelligence (AI) plays a more and more important role in our everyday life due to the
advantages that it brings when used, such as 24/7 availability, a very low percentage of …
advantages that it brings when used, such as 24/7 availability, a very low percentage of …
A robust heart disease prediction system using hybrid deep neural networks
Heart Disease (HD) is recognized as the leading cause of worldwide mortality by the World
Health Organization (WHO), resulting in the loss of approximately 17.9 million lives each …
Health Organization (WHO), resulting in the loss of approximately 17.9 million lives each …
Convective flow dynamics with suspended carbon nanotubes in the presence of magnetic dipole: Intelligent solution predicted Bayesian regularization networks
This paper narrates an investigation for the convective flow dynamics involving single and
multiwall carbon nanotubes as well as methanol hybrid nanofluids in the presence of …
multiwall carbon nanotubes as well as methanol hybrid nanofluids in the presence of …
Genetic Programming‐Based Feature Selection for Emotion Classification Using EEG Signal
The COVID‐19 has resulted in one of the world's most significant worldwide lock‐downs,
affecting human mental health. Therefore, emotion recognition is becoming one of the …
affecting human mental health. Therefore, emotion recognition is becoming one of the …
Using an artificial neural network model for natural gas compositions forecasting
The paper presents the results of natural gas composition forecasting obtained using the
MLP model of artificial neural network. The training of MLP model was performed on the …
MLP model of artificial neural network. The training of MLP model was performed on the …
A review of recent developments in the application of machine learning in solar thermal collector modelling
M Vakili, SA Salehi - Environmental Science and Pollution Research, 2023 - Springer
Over the past few decades, the popularity of solar thermal collectors has increased
dramatically because of many significant advantages like being a free, natural …
dramatically because of many significant advantages like being a free, natural …