A novel approach based on recurrent neural networks applied to nonlinear systems optimization

Registro completo de metadados
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorda Silva, Ivan Nunes-
Autor(es): dc.creatordo Amaral, Wagner Caradori-
Autor(es): dc.creatorde Arruda, Lucia Valeria-
Data de aceite: dc.date.accessioned2021-03-10T16:48:42Z-
Data de disponibilização: dc.date.available2021-03-10T16:48:42Z-
Data de envio: dc.date.issued2014-05-20-
Data de envio: dc.date.issued2014-05-20-
Data de envio: dc.date.issued2007-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.apm.2005.08.007-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/8885-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/8885-
Descrição: dc.descriptionThis paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. 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 that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.-
Formato: dc.format78-92-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier B.V.-
Relação: dc.relationApplied Mathematical Modelling-
Relação: dc.relation2.617-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectnonlinear optimization problems-
Palavras-chave: dc.subjectrecurrent neural networks-
Palavras-chave: dc.subjectHopfield networks-
Palavras-chave: dc.subjectnonlinear programming-
Título: dc.titleA novel approach based on recurrent neural networks applied to nonlinear systems optimization-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.