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VI Brazilian Symposium on Neural Networks (SBRN'00)
A Novel Approach for Solving Constrained Nonlinear Optimization Problems Using Neurofuzzy Systems
Rio de Janeiro, Brazil
January 22-January 25
ISBN: 0-7695-0856-1
ASCII Text
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Ivan Nunes da Silva, André Nunes de Souza, Mário Eduardo Bordon, "A Novel Approach for Solving Constrained Nonlinear Optimization Problems Using Neurofuzzy Systems," Neural Networks, Brazilian Symposium on, pp. 213, VI Brazilian Symposium on Neural Networks (SBRN'00), 2000.
 
 
BibTex
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@article{ 10.1109/SBRN.2000.889741,
author = {Ivan Nunes da Silva and André Nunes de Souza and Mário Eduardo Bordon},
title = {A Novel Approach for Solving Constrained Nonlinear Optimization Problems Using Neurofuzzy Systems},
journal ={Neural Networks, Brazilian Symposium on},
volume = {0},
year = {2000},
issn = {1522-4899},
pages = {213},
doi = {http://doi.ieeecomputersociety.org/10.1109/SBRN.2000.889741},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Neural Networks, Brazilian Symposium on
TI - A Novel Approach for Solving Constrained Nonlinear Optimization Problems Using Neurofuzzy Systems
SN - 1522-4899
SP
EP
A1 - Ivan Nunes da Silva,
A1 - André Nunes de Souza,
A1 - Mário Eduardo Bordon,
PY - 2000
VL - 0
JA - Neural Networks, Brazilian Symposium on
ER -
 
Ivan Nunes da Silva, State University of S?o Paulo
André Nunes de Souza, State University of S?o Paulo
Mário Eduardo Bordon, State University of S?o Paulo
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.
Citation:
Ivan Nunes da Silva, André Nunes de Souza, Mário Eduardo Bordon, "A Novel Approach for Solving Constrained Nonlinear Optimization Problems Using Neurofuzzy Systems," sbrn, pp.213, VI Brazilian Symposium on Neural Networks (SBRN'00), 2000
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