Abstract The Particle Swarm Optimization technique (PSO) is widely used in practical
applications due to its flexibility and strong optimization performance. However, like other …

Computed tomography (CT) is used in a wide range of medical imaging diagnoses.
However, the reconstruction of CT images from raw projection data is inherently complex …

In recent years, many researchers have made a continuous effort to develop new and
efficient meta-heuristic algorithms to address complex problems. Hence, in this study, a …

The complexity of equivalent circuit models of photovoltaic cells and modules poses a
difficult task to the parameter extraction methods. Teaching-learning-based optimization …

Convolutional neural networks (CNNs) have excelled in artificial intelligence, particularly in
image-related tasks such as classification and object recognition. However, manually …

Nowadays, different types of non-linear and multi-modal hybridized alternating current (AC)
power grids with multi-terminal high voltage direct current (HVDC) are of great importance …

Feature selection is a pivotal preprocessing step in deploying machine learning solutions,
aimed at removing redundant features from datasets while preserving predictive accuracy …

In the evolving landscape of early childhood education, the integration of technology has
emerged as a significant paradigm shift. This study focuses on this shift, presenting the …

In recent years, many meta‐heuristic algorithms have been investigated to estimate the
parameters of photovoltaic (PV) models. However, the accuracy of the estimated parameters …

Abstract Arithmetic Optimization Algorithm (AOA) is widely used to solve global optimization
problems. However, it often faces premature convergence challenges in complex …