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A fast electric load forecasting using adaptive neural networks
(2003-12-01)
This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, ...
A fast electric load forecasting using adaptive neural networks
(2003-12-01)
This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, ...
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. ...
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. ...
Neural networks training using the constructivism paradigms
(1995-12-01)
The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural ...
Neural networks training using the constructivism paradigms
(1995-12-01)
The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural ...
Applying Bayesian Regularization for Acceleration of Levenberg-Marquardt based Neural Network Training
Neural network is widely used for image classification problems, and is proven to be effective with high successful rate. However one of its main challenges is the significant amount of time it takes to train the network. ...
EM-Based Optimization of Microwave Circuits using Artificial Neural Networks
(IEEE MTT-S Int. Microwave Symp. Workshop Notes and Short Courses, 2013)