A crucial problem in non-linear time series forecasting is to determine its auto-regressive order, in particular when the prediction method is non-linear. We show in this paper tha...
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
—We propose to use multiscale entropy analysis in characterisation of network traffic and spectrum usage. We show that with such analysis one can quantify complexity and predict...