Particle Swarm Optimization Approach for Multi-step-ahead Prediction Using Radial Basis Function Neural Network

An alternative approach, between much others, for mathematical representation of dynamics systems with complex or chaotic behaviour, is a radial basis function neural network using k-means for clustering and optimized by pseudo-inverse and particle swarm optimisation. This paper presents the implementation and study to identify a dynamic system, with nonlinear and chaotic behaviour, called Rössler’s circuit, with concepts of multi-step-ahead prediction. Copyright © 2005 IFAC

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