The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that mot...
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Evolutionary Artificial Neural Networks (EANN) have been a focus of research in the areas of Evolutionary Algorithms (EA) and Artificial Neural Networks (ANN) for the last decade. ...
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ...