The last 10 years have witnessed the growth of artificial intelligence into different research
areas, emerging as a vibrant discipline with the capacity to process large amounts of …

The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …

Objective In this research paper, the brain MRI images are going to classify by considering
the excellence of CNN on a public dataset to classify Benign and Malignant tumors …

The difficulty and complexity of the real-world numerical optimization problems has grown
manifold, which demands efficient optimization methods. To date, various metaheuristic …

In this paper, we propose a new metaheuristic algorithm based on Lévy flight called Lévy
flight distribution (LFD) for solving real optimization problems. The LFD algorithm is inspired …

Feature selection (FS) represents an optimization problem that aims to simplify and improve
the quality of highly dimensional datasets through selecting prominent features and …

The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …

Feature selection is a required preprocess stage in most of the data mining tasks. This paper
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …

Feature selection, an optimization problem, becomes an important pre-process tool in data
mining, which simultaneously aims at minimizing feature-size and maximizing model …

Timely and effective fault detection is essential to ensure the safe and reliable operation of
wind turbines. However, due to the complex kinematic mechanisms and harsh working …