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The Artificial neural networks are relatively crude electronic networks of "neurons" based on the neural structure of the brain. It process the records one at a time, and "learn" by comparing their prediction of the record with the known actual record. The errors from the initial prediction of the first record is fed back into the network, and used to modify the networks algorithm...
A neural networks are able to give solutions to complex problems in business intelligence and financial engineering due to their nonlinear processing. This paper consists of a survey of various business intelligence and financial engineering and so on applications based on the neural networks, and also a summary of the recent techniques such as still evolutionary algorithms, cellular computing, Bayesian...
In this work new improvements from a previous approach of an automatic design of artificial neural networks applied to forecast time series is tackled. The automatic process to design artificial neural networks is carried out by a genetic algorithm. These improvements, in order to get an accurate forecasting, are related with: to shuffle train and test patterns obtained from time series values and...
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