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 …

Wind power is playing a pivotal part in global energy growth as it is clean and pollution‐free.
To maximize profits, economic scheduling, dispatching, and planning the unit commitment …

An artificial neural network (ANN) that mimics the information processing mechanisms and
procedures of neurons in human brains has achieved a great success in many fields, eg …

In this paper, to compute the firing strength values of type-2 fuzzy models, a soft version of
minimum is presented, which endows the fuzzy model with the ability to solve large …

Some recent research reports that a dendritic neuron model (DNM) can achieve better
performance than traditional artificial neuron networks (ANNs) on classification, prediction …

Interval type-2 fuzzy neural networks (IT2FNNs) can be seen as the hybridization of interval
type-2 fuzzy systems (IT2FSs) and neural networks (NNs). Thus, they naturally inherit the …

In this study, the control problem of complex robot system with uncertainties and
disturbances is addressed. Fuzzy system-fuzzy neural network-backstepping control (FS …

In the neural network adaptation, the Newton method could find a minimum with its second-
order partial derivatives, and convergent gradient steepest descent could assure its error …

Text obtained in natural scenes contains various information; therefore, it is extensively used
in various applications to understand the image scenarios and also to retrieve the visual …

Detecting anomaly of chest X-ray images by advanced technologies, such as deep learning,
is an urgent need to improve the work efficiency and diagnosis accuracy. Fine-tuning …