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استعمال السلاسل الزمنية والشبكات العصبية الاصطناعية للتنبؤات المستقبلية لمستوى التضخم في العراق == The Use of Time Series And Neural Network Prediction Futurism Level Swelling In Iraq
Author name:
قصي عصام حميد الزبيدي
Supervisor name:
قاسم محمد علي
General topic:
Administration and Economics
Specific topic:
Applied Statistics
Degree:
Higher Diploma
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T3968 - p.pdf
Abstract:
لقد شهد الاقتصاد العراقي ارتفاعات مستمرة ومتزايدة في معدلات التضخم والتي وصلت الى مستوى التضخم الجامح مما اثرت على نمط الانتاج والاستثمار والاستهلاك والادخار ونمط تخصيص الموارد وتوزيع الدخل، نتيجة للظروف القاسية التي مر بها العراق وقد استعملت وسائل احصائ | It is known that the most important countries of evolution is the process of planning and the detailed plans the future and this requires the adoption of advanced statistical methods.We discussed this adopts the first focus method of time series Box - Jenkins and which takes into account the temporal variations in the study of phenomena, analyze and identify the most important properties in the construction of appropriate models of the phenomenon being studied, as has been the adoption of key stages in building models of chains of time from diagnosis until the development of the form timely and predictable phenomenon studied.Second, neural networks and included the study of this simplified the basic concepts of neural networks He addressed the most important types of neural networks is a network deployment rear (Back Propagation) algorithms and their own learning.The practical side has been the use of real data to calculate the rate of inflation based on the indices for commodity groups for a period of five years by months(2007 - 2011) Based on the results of time series Box - Jenkins and neural networks shows that the method of artificial neural networks more flexible and higher efficiency in the analysis and forecasting
