HIGHLIGHTS
SUMMARY
There are several previous attempts at predicting resource usage using deep learning techniques, however they focus on a single method, such as Recurrent Neural_Networks (RNNs) in the case of Dugann et_al or using very specific architectures, such as restricted Boltzmann machines. This technique really benefited when researchers started experimenting with the combination of ARIMA and computational intelligence algorithms, such as artificial neural_networks and support vector machines. More recently, deep artificial neural_networks have been widely successful in timeseries analysis applied to financial data, such as the price of gold being accurately predicted by using convolutional . . .
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