الفهرس 
ملخص الرسالة باللغة العربيةيوجد فقط 14 صفحة متاحة للعرض العام
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المستخلص
Forecasting plays an important role in our daily life, as predictions of future events are important in the decision-making process in all fields of life. It is often difficult to have predictions identical to actual values; therefore, attention is focused on improving the accuracy of forecasts as much as possible. There are many types of forecasting methods that are commonly used, in particular different models whether traditional or modern models, recent studies show that modern methods of forecasting tend to improve prediction accuracy, but there is no clear evidence showing that any model can always outperform other models in the accuracy of prediction. In this paper, we compare two methods of forecasting, the first method is Fuzzy Time Series using two models Chen and Yu, and box-Jenkins models. The results revealed that the Fuzzy Time Series Models perform better with respect to prediction accuracy than box-Jenkins models when applied to monthly Egyptian exports data (2007-2015).