Abstract Marine Predators Algorithm (MPA) is a recent nature-inspired optimizer stemmed
from widespread foraging mechanisms based on Lévy and Brownian movements in ocean …

Abstract Marine Predators Algorithm (MPA) is the existing population-based meta-heuristic
algorithms that falls under the category of Nature-Inspired Optimization Algorithm (NIOA) …

A novel metaheuristic called Chaotic Marine Predators Algorithm (CMPA) is proposed and
investigated for the optimization of engineering problems. CMPA integrates the exploration …

This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …

As the volume of data generated by information systems continues to increase, machine
learning (ML) techniques have become essential for the extraction of meaningful insights …

In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …

In this paper, a hybrid feature selection algorithm based on a multi-objective algorithm with
ReliefF (MOFS-RFGA) is proposed. Combining the advantages of filter and wrapper …

Feature Selection (FS) techniques extract the most recognizable features for improving the
performance of classification methods for medical applications. In this paper, two intelligent …

Reducing pollutant emissions from electricity production in the power system positively
impacts the control of greenhouse gas emissions. Boosting kernel search optimizer (BKSO) …

Suspensions containing microencapsulated phase change materials (MPCMs) play a
crucial role in thermal energy storage (TES) systems and have applications in building …