Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
Abstract. In this paper we present an estimation of distribution particle swarm optimization algorithm that borrows ideas from recent developments in ant colony optimization. In th...
Particle Swarm Optimization (PSO) has received increased attention in the optimization research community since its first appearance. Regarding multi-objective optimization, a con...
This paper proposes an integrated approach to arrive at optimal build orientations, simultaneously minimizing surface roughness ‘Ra’ and build time ‘T’, for object manufac...
Abstract. This paper describes a Swarm Granulator, a new application of particle swarms to sound synthesis. Granulation, an established technique in sound synthesis, depends on man...
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
This paper presents an efficient technique of designing twodimensional IIR digital filters using a new algorithm involving the tightly coupled synergism of particle swarm optimiza...
Particle Swarm Optimization (PSO) technique proved its ability to deal with very complicated optimization and search problems. This paper proposes a new particle swarm variant whi...
The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous ...
Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continu...