Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Particle swarm optimization (PSO) is a stochastic algorithm used for the optimization
problems proposed by Kennedy [1] in 1995. It is a very good technique for the optimization …

Moth-flame optimization (MFO) is a widely used nature-inspired algorithm characterized by a
simple structure with simple parameters. However, for some complex optimization tasks …

Earthworms can aerate the soil with their burrowing action and enrich the soil with their
waste nutrients. Inspired by the earthworm contribution in nature, a new kind of bio-inspired …

Real life optimization problems require techniques that properly explore the search spaces
to obtain the best solutions. In this sense, it is common that traditional optimization …

This paper focuses on the study of multilevel COVID-19 X-ray image segmentation based on
swarm intelligence optimization to improve the diagnostic level of COVID-19. We present a …

In classification, feature selection is an important data pre-processing technique, but it is a
difficult problem due mainly to the large search space. Particle swarm optimisation (PSO) is …

Particle swarm optimization (PSO) has been shown to yield good performance for solving
various optimization problems. However, it tends to suffer from premature convergence …

Abstract Salp Swarm Algorithm (SSA) is a recent approach with a simple implementation,
few parameters, and low computational cost. SSA has been used in different optimization …

We propose a novel variation to biogeography-based optimization (BBO), which is an
evolutionary algorithm (EA) developed for global optimization. The new algorithm employs …