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Electric load forecasting using a fuzzy ART&ARTMAP neural network
(Elsevier B.V., 2005-01-01)
This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ...
Development of neurofuzzy architecture for solving the N-Queens problem
(Taylor & Francis Ltd, 2005-11-01)
Neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent ...
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 ...
Morphological bidirectional associative memories
(Pergamon-elsevier Science LtdOxfordInglaterra, 1999)
Avaliação estatística de métodos de poda aplicados em neurônios intermediários da rede neural MLP
(2006-12-01)
There are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved ...
Shape, connectedness and dynamics in neuronal networks
(Elsevier BVAmsterdam, 2013-11)
The morphology of neurons is directly related to several aspects of the nervous system, including its connectedness, health, development, evolution, dynamics and, ultimately, behavior. Such interplays of the neuronal ...
Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems
(Elsevier B.V., 2011-01-01)
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. ...
Artificial neural network model of discharge lamps in the power quality context
(2013-06-01)
This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of ...
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 ...