… Also note, for reasons of space, articles which have investigated/applied PSO for/to a
specific application, such as solving the knapsack problem (Bonyadi and Michalewicz, 2012) or …

Seizure prediction has attracted growing attention as one of the most challenging predictive
data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic …

There are some questions concerning the applicability of meta-heuristic methods for real-world
problems; further, some researchers claim there is a growing gap between research and …

In this paper, we investigate three important properties (stability, local convergence, and
transformation invariance) of a variant of particle swarm optimization (PSO) called standard …

Real-world optimization problems often consist of several NP-hard optimization problems
that interact with each other. The goal of this paper is to provide a benchmark suite that …

In this paper, the underlying assumptions that have been used for designing adaptive particle
swarm optimization (PSO) algorithms in the past years are theoretically investigated. I …

In this paper, we investigate movement patterns of a particle in the particle swarm optimization
(PSO) algorithm. We characterize movement patterns of the particle by two factors: 1) the …

In this letter, we study the first- and second-order stabilities of a stochastic recurrence relation
that represents a class of particle swarm optimization (PSO) algorithms. We assume that …

Several well-studied issues in the particle swarm optimization algorithm are outlined and
some earlier methods that address these issues are investigated from the theoretical and …

Many outstanding studies have reported promising results in seizure forecasting, one of the
most challenging predictive data analysis problems. This is mainly because …