1 publication

• Published Subscription 13 Feb 2019

  The Comparison in Time Series Forecasting of Air Traffic Data by Autoregressive Integrated Moving Average Model, Radial Basis Function and Elman Recurrent Neural Networks

  By R. Ramakrishna, Berhe Aregay, Tewodros Gebregergs

  Abstract: Nowadays, nonlinear time series and artificial neural networks (ANN) models are used for forecasting in the field of business, agriculture and soon. Recent studies have shown, ANN have been successfully used for forecasting of financial and agriculture data series The classical methods used for time series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and outputs. ANN have more advantages that can approximate to …

  Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 75–90 Read article →