Seasonal decomposition and forecasting of telecommunication data: A comparative case study |
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| Authors: | Constantinos S. Hilas [Author Vitae] Sotirios K. Goudos [Author Vitae] John N. Sahalos [Author Vitae] |
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| Affiliation: | a Department of Informatics and Communications, Technological Educational Institute of Serres, Terma Magnisias, GR-62124, Serres, Greece
b Radiocommunications Laboratory, Department of Physics, Aristotle University of Thessaloniki, GR-54124, Thessaloniki, Greece |
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| Abstract: | In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University. |
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| Keywords: | Forecast evaluation Seasonal adjustment Time series Call data pattern recognition Model selection |
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