Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …

Blood is made up of leukocytes (WBCs), erythrocytes (RBCs), and thrombocytes. The ratio of
blood cancer diseases is increasing rapidly, among which leukemia is one of the famous …

The use of metaheuristics is widespread for optimization in both scientific and industrial
problems due to several reasons, including flexibility, simplicity, and robustness. Grey Wolf …

Feature selection (FS) is considered to be a hard optimization problem in data mining and
some artificial intelligence fields. It is a process where rather than studying all of the features …

Rapid data growth presents many challenges for Machine Learning (ML) tasks as it can
include lots of irrelevant, noisy, and redundant features. Thus, it is vital to select the most …

Feature selection (FS) methods are necessary to develop intelligent analysis tools that
require data preprocessing and enhancing the performance of the machine learning …

Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …

A novel optimization algorithm called the optical microscope algorithm (OMA) is developed
and applied in this study. Drawing inspiration from the magnification capabilities of an …

Unmanned aerial vehicles are applied extensively in various fields due to their advantages
of low-cost, high-maneuverability, and easy-operation. However, the path planning problem …

This paper presents a hybrid evolutionary algorithm, cultural-particle swarm optimization (C-
PSO), which is inspired by the cultural algorithm and the particle swarm optimization …