Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

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 …

This study presents the analysis and principle of an innovative optimizer named weIghted
meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean …

Despite the simplicity of the whale optimization algorithm (WOA) and its success in solving
some optimization problems, it faces many issues. Thus, WOA has attracted scholars' …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

The grasshopper optimization algorithm is one of the dominant modern meta-heuristic
optimization algorithms. It has been successfully applied to various optimization problems in …

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 …

This paper completely introduces an exhaustive and a comprehensive review of the so-
called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of …

The output power–voltage (P–V) curve of a solar photovoltaic (PV) power system shows a
single peak under an even irradiation environment, nevertheless, but often exhibits seriously …