An Application of Artificial Neural Networks for Prediction and Comparison with Statistical Methods

S. Ballı, İ. Tarımer


The unemployment rate is a measure of the prevalence of unemployment and can be a good indication of the for country’s economic situation. It is thought that it might change depending upon educational situations of the people. This study seeks how to model and predict the unemployment rates with respect to educational situations of the people in Turkey. For this purpose, An Artificial Neural Networks model was proposed for prediction long-term prediction (up to year 2019) is performed by using Artificial Neural Networks, Box-Jenkins Method and Regression Analysis Method. Then these methods have been compared with each other; and the study concludes that Artificial Neural Networks is more appropriate and consistent than Box-Jenkins Method or Regression Analysis Method for the prediction.



Artificial neural networks; prediction; Box-Jenkins method; regression analysis method

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Print ISSN: 1392-1215
Online ISSN: 2029-5731