— We extend the Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) by collaborative concepts from Particle Swarm Optimization (PSO). The proposed Particle Swarm CMA-ES...
New Particle Swarm Optimization (PSO) methods for dynamic and noisy function optimization are studied in this paper. The new methods are based on the hierarchical PSO (H-PSO) and a...
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— Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) a...
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 ...