The performance evaluation of a Photovoltaic (PV) system heavily relies on accurately
estimating the parameters based on its current—voltage relationships. However, due to the …

Artificial neural networks (ANNs) have achieved great success in performing machine
learning tasks, including classification, regression, prediction, image processing, image …

Differential evolution (DE) is a popular optimization algorithm with easy implementation and
fast convergence rate. For evolutionary algorithms such as DE, the initialization process of …

Many real-world engineering problems such as machining processes are multi-objective
optimization problems (MOPs) because multiple performance characteristics are considered …

In the recent highly saturated, fluctuated as well as competitive marketing situation,
economic growth, stability and survival of a manufacturing company are substantial factors …

The paper considers the issues of implementing an adaptive testing system using artificial
neural network modules, which should resolve the problem of intellectual selection of the …

In this paper, a multi-strategy fusion enhanced Honey Badger algorithm (EHBA) is proposed
to address the problem of easy convergence to local optima and difficulty in achieving fast …

This study introduces ETLBOCBL-CNN, an automated approach for optimizing convolutional
neural network (CNN) architectures to address classification tasks of varying complexities …

Feedfoward neural network (FNN) is popular machine learning technique widely
implemented for image classification, data clustering, object recognition, etc. due to its …

Feature selection is a popular pre-processing technique applied to enhance the learning
performances of machine learning models by removing irrelevant features without …