Examples of using The artificial neural in English and their translations into Portuguese
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used to select and preserve the points that better characterize the waveform contoursa and the artificial neural network is used in the compression of other points as well as on the signal reconstruction process.
jenkins(arima method), the artificial neural networks radial basis functions
where the principal models are the artificial neural networks(ann) and fuzzy inference systems fis.
In order to improve the artificial neural networks(ann) learning of multi-layer perceptron type, this paper describes
One of the techniques that have been successful in generating the estimates is the artificial neural networks(ann). the neural modeling has allowed both the prediction of different geotechnical soil attributes as their locations with relative accuracy for a given study area.
On this basis of information was created a mathematical model based on the artificial neural networks method, capable of predicting the pressure inside the travelling grate furnace,
An alternative to a more realistic assessment of the settlements in deep foundations consists in the application of the artificial neural networks, models that work analogically in the human brain which have been recently contributing to the resolution of complex problems in different areas of civil engin.
in addition to the artificial neural networks which allow complex input data.
However, the artificial neural networks(ann) has been increasingly used technique for modeling complex problems,
among which the most popular are the artificial neural networks ann.
This paper describes the utilization of the artificial neural networks(ann) technique, with the error backpropagation trainning algorithm,
hybrid intelligent tutoring system(hits) already proposed in the literature that uses the artificial neural networks mlp(multi layer perceptron)
This work included the use of artificial neural networks as a comparison parameter between metamodels.
Was also used the technique of artificial neural networks- anns in step quantification of damage.
CONCLUSIONS: The artificial neural network showed good predictive ability,
Studies on the use of artificial neural networks.