Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

The vast majority of today's data is collected and stored in enormous databases with a wide
range of characteristics that have little to do with the overarching goal concept. Feature …

In this article, an Improved Grey Wolf Optimizer (I-GWO) is proposed for solving global
optimization and engineering design problems. This improvement is proposed to alleviate …

This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …

This paper proposes a new population-based optimization algorithm called hunter–prey
optimizer (HPO). This algorithm is inspired by the behavior of predator animals such as …

Image denoising faces significant challenges, arising from the sources of noise. Specifically,
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …

There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …

In this paper, a novel population-based, nature-inspired optimization paradigm is proposed,
which is called Harris Hawks Optimizer (HHO). The main inspiration of HHO is the …

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 …