A semisupervised classification method based on particle swarm optimization (PSO) is
proposed. The semisupervised PSO simultaneously uses limited labeled samples and large …

In this article it is studied the application of a genetic algorithm in the problem of variable
selection for multiple linear regression, minimizing the least squares criterion. The algorithm …

We have evaluated five metaheuristics of combinatorial optimization applied in clustering by
partitions: simulated annealing, tabu search, genetic algorithm, ant colonies and particle …

This paper proposes and evaluates a Particle Swarm Optimization (PSO) based ensemble
classifier. The members of the ensemble are Nearest Prototype Classifiers generated …

We propose a novel method for building fuzzy clusters of large data sets, using a smoothing
numerical approach. The usual sum-of-squares criterion is relaxed so the search for good …

Adopt the concept of mutation in Genetic Algorithm to improve Particle Swarm Optimization.
The experimental results show tow advantages for the mutation strategies. Firstly, It's …