Title :
Training matrix parameters by Particle Swarm Optimization using a fuzzy neural network for identification
Author :
Shafiabady, Niusha ; Teshnehlab, M. ; Shooredeli, M. Aliyari
Author_Institution :
Dept. of Mechatron. Eng. Technol., Azad Univ. Sci. & Res. center, Tehran
Abstract :
In this article particle swarm optimization that is a population-based method is applied to train the matrix parameters that are standard deviation and centers of radial basis function fuzzy neural network. We have applied least square and recursive least square in training the weights of this fuzzy neural network.There are four sets of data used to examine and prove that particle swarm optimization is a good method for training these complicated matrices as antecedent part parameters.
Keywords :
fuzzy neural nets; least squares approximations; matrix algebra; particle swarm optimisation; radial basis function networks; fuzzy neural network; least square methods; particle swarm optimization; population-based method; radial basis function fuzzy neural network; recursive least square methods; training matrix parameters; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Intelligent networks; Intelligent systems; Least squares methods; Mechatronics; Neurons; Nonlinear control systems; Particle swarm optimization; Identification; Least Square; Particle Swarm Optimization; Radial Basis Function Fuzzy Neural Network; Recursive Least Square;
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
DOI :
10.1109/ICIAS.2007.4658372
