Title :
Optimization of hierarchical neural fuzzy models
Author :
Campello, Ricardo J G B ; Amaral, Wagner C.
Author_Institution :
DCA, UNICAMP, Campinas, SP, Brazil
Abstract :
Hierarchical fuzzy structures were introduced in previous work to deal with the dimensionality problem which is the main drawback to the application of neural networks and fuzzy models in the modeling and control of large-scale systems. In the present paper, the use of Radial Basis Function (RBF) networks connected in a hierarchical (cascade) fashion is investigated. The RBF networks are formulated as simplified fuzzy systems and the backpropagation equations for the optimization of the resulting hierarchical models are derived from this formulation. The optimization of the models using the conjugate gradient algorithm of Fletcher and Reeves is proposed and illustrated by means of a numerical example
Keywords :
fuzzy neural nets; optimisation; radial basis function networks; Radial Basis Function; cascade; conjugate gradient; fuzzy models; hierarchical; large-scale systems; neural fuzzy models; neural networks; Control system synthesis; Electronic mail; Equations; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Large-scale systems; Mathematical model; Neural networks; Radial basis function networks;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.861427
