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Projeto E análise de uma rede neural para resolver problemas de programação dinâmica
(2001-01-01)
Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Neural networks with ...
Distribution network planning using a constructive heuristic algorithm
(2009-12-01)
An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining ...
Distribution network planning using a constructive heuristic algorithm
(2009-12-01)
An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining ...
Recurrent neural networks with fixed time convergence for linear and quadratic programming
(Institute of Electrical and Electronics Engineers, 2013-08-04)
Recurrent neural networks with fixed time convergence for linear and quadratic programming
(Institute of Electrical and Electronics Engineers, 2013-08-04)
An extended goal programming methodology for analysis of a network encompassing multiple objectives and stakeholders
(2016-12-01)
This paper proposes a goal programming methodology to ensure that a mix of balance and optimisation is achieved across a hierarchical decision network. The extended goal programming principle is used for this purpose. A ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This 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 ...
Design and analysis of an efficient neural network model for solving nonlinear optimization problems
(Taylor & Francis Ltd, 2005-10-20)
This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are ...
A novel approach based on recurrent neural networks applied to nonlinear systems optimization
(Elsevier B.V., 2007-01-01)
This 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 ...