A novel approach based on recurrent neural networks applied to nonlinear systems optimization
type: Item
instance of: scholarly article
title: A novel approach based on recurrent neural networks applied to nonlinear systems optimization
zbMATH Open document ID: 1152.90616
author: Ivan Nunes da Silva
author: W. C. do Amaral
author: Lucia Valeria de Arruda
published in: Applied Mathematical Modelling
publication date: 2008-05-19T00:00:00Z
full work available at URL: http://hdl.handle.net/11449/8885
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90B10
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 5276439
zbMATH Keywords: nonlinear optimization problems
zbMATH Keywords: recurrent neural networks
zbMATH Keywords: Hopfield networks
zbMATH Keywords: nonlinear programming
MaRDI profile type: Publication
OpenAlex ID: W2059006875
cites work: Q3134873
cites work: A projection neural network and its application to constrained optimization problems
cites work: Multilayer perceptron for nonlinear programming
cites work: An efficient model of neural networks for dynamic programming
cites work: A novel approach to robust parameter estimation using neurofuzzy systems
cites work: Neurons with graded response have collective computational properties like those of two-state neurons.
cites work: Global convergence and suppression of spurious states of the Hopfield neural networks
cites work: Q3141919
cites work: An approach to nonlinear programming
DOI: 10.1016/J.APM.2005.08.007
description: scientific article; zbMATH DE number 5276439