This paper introduces a novel meta-heuristic optimization algorithm named Clustering
Wavelet Opposition-based Marine Predators Algorithm (CWOMPA) to address some …

Abstract The Marine Predators Algorithm (MPA) is a novel hunting-based optimizer. The
MPA's central concept is based on the well-known Lévy Flight (LF) and Brownian Motion …

The application of metaheuristic algorithms is one of the most promising approaches for
solving real-world problems. The marine predators algorithm (MPA) is a recently proposed …

Feature Selection (FS) reduces the number of features by removing unnecessary,
redundant, and noisy information while keeping a relatively decent classification accuracy …

This paper presents a nature-inspired metaheuristic called Marine Predators Algorithm
(MPA) and its application in engineering. The main inspiration of MPA is the widespread …

Marine predators algorithm (MPA) is a recently proposed metaheuristic algorithm that
mimics the marine predators behavior when attacking their preys. Recently, the MPA has …

Abstract Marine Predators Algorithm (MPA) is a newly nature-inspired meta-heuristic
algorithm, which is proposed based on the Lévy flight and Brownian motion of ocean …

Feature selection (FS) is applied to reduce data dimensions while retaining much
information. Many optimization methods have been applied to enhance the efficiency of FS …

Marine predator algorithm (MPA) is a powerful metaheuristic optimization algorithm that
shows effective convergence ability on complex benchmark functions. The combination of …

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