Optimisation-based methods are enormously used in the field of data classification. Particle
Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely …

In recent years, there has been a growing interest in applying Particle Swarm Optimization
(PSO) to data classification. Nonetheless, due to the curse of dimensionality, the …

With the rapid development of technologies such as the internet, the amount of data that are
collected or generated in many areas such as in the agricultural, biomedical, and finance …

In many fields such as signal processing, machine learning, pattern recognition and data
mining, it is common practice to process datasets containing huge numbers of features. In …

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 …

This paper describes a novel Particle Swarm Optimization (PSO)-based classification
algorithm with improved capabilities in comparison to several alternatives. The algorithm …

Feature selection is an important but difficult task in classification, which aims to reduce the
number of features and maintain or even increase the classification accuracy. This paper …

This paper offers a survey of recent work on particle swarm classification (PSC), a promising
offshoot of particle swarm optimization (PSO), with the goal of positioning it in the overall …

In classification, feature selection is an important, but difficult problem. Particle swarm
optimisation (PSO) is an efficient evolutionary computation technique. However, the …

Abstract Particle Swarm Optimization (PSO) is a well-known swarm intelligence (SI)
algorithm employed for solving various optimization problems. This algorithm suffers from …