Advanced Time Series Forecasting Methods
Pp. 3-10 (8)
Cagdas Hakan Aladag and Erol Eǧrioǧlu
The researchers from various fields have been studying on time series forecasting for
approximately one century in order to get better forecasts for the future. To achieve high forecast
accuracy level, various time series forecasting approaches have been improved in the literature. During
1980s, some crucial developments happened and time series researches changed. More sophisticated
algorithms could be improved since properties of computers were enhanced. Therefore, new time series
forecasting approaches such as artificial neural networks and fuzzy time series could be proposed. In
the applications, these approaches have proved its success in forecasting real life time series. In
addition, hybrid forecasting methods which combine these new approaches have also been improved to
obtain more accurate forecasts. In recent years, these advanced time series forecasting methods have
been used to forecast real life time series and satisfactory results have also been obtained.
Artificial neural networks, Fuzzy time series, Forecasting, Hybrid methods.
Hacettepe University, Faculty of Science, Department of Statistics, 06800, Ankara, Turkey