Particle Swarm Optimization to Improve Neural Identifiers for Discrete-time Unknown Nonlinear Systems
Abstract
Chapter 6 presents the application of bio-inspired algorithms to improve neural identifiers for discrete-time unknown nonlinear systems. PSO is particularly used to improve two kinds of neural identifiers: first, PSO is used to find initial conditions of an EKF learning algorithm (enhanced PSO-EKF) to train a RHONN in order to identify a dynamic mathematical model of a linear induction motor benchmark; second, the enhanced PSO-EKF is used to train a recurrent multilayer perceptron in order to obtain an accurate neural model for forecasting in smart grids. Importance of these applications is attributable to the need ...
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