Mat. Res. vol.17 número5

In this study, an artificial neural network method using the back-propagation algorithm was proposed for the prediction of ferric iron precipitation in uranium bioleaching

All artificial neural networks used in this work showed high accuracy to estimate the moisture, however, the neural network based on the basic density and drying days was the

Abstract – The purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes based on the training of an artificial neural

A back propagation artificial neural networks (BPANN) was used for estimating the velocity of the geodetic densification points as an alternative tool to the interpolation methods

In the present work, the development of a nonlinear controller, based on a neural network inverse model (ANN controller), was proposed and tested to manipulate

Method: A neuro-fuzzy system was developed using the NEFCLASS (NEuro Fuzzy CLASSIfication) architecture and an artificial neural network with backpropagation learning

The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead

Unsupervised learning is a machine learning technique that sets parameters of an artificial neural network based on given data and a cost function which is to be