A novel approach for solving constrained nonlinear optimization problems using neurofuzzy systems.
Int J Neural Syst
; 11(3): 281-6, 2001 Jun.
Article
em En
| MEDLINE
| ID: mdl-11577380
A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Redes Neurais de Computação
/
Lógica Fuzzy
/
Dinâmica não Linear
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Int J Neural Syst
Assunto da revista:
ENGENHARIA BIOMEDICA
/
INFORMATICA MEDICA
Ano de publicação:
2001
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Singapura