Regression analysis, artificial neural network models were used as a non-linear model to compare results and detect more accurate model.

Moscow-based mathematicians Kuzmina, Manykin, and Grichuk describe and analyze various oscillatory neutral network models, a special kind of artificial neural network model that helps elucidate the basic principles of brain performance by displaying the capability and limitations of synchronization-based information processing.

CANDACE uses sophisticated image processing, feature extraction, pattern classification and artificial neural network techniques to produce a diagnosis.

Self Organizing Feature Maps [1] are special class of artificial neural networks based on competitive learning.

Uncertainty treatment using paraconsistent logic; introducing paraconsistent artificial neural networks.

There are many methods how to predict, one of them is utilization of artificial neural networks (ANNs).

Researchers in Spain indicate that an artificial neural network could be used to obtain a temperature prediction model for high-pressure processes.

The artificial neural network is trained for a set of normalized inputs and tested.