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Türkiye de Enflasyonun İleri ve Geri Beslemeli Yapay Sinir Ağlarının Melez Yaklaşımı ile Öngörüsü
Author(s) -
Necati Alp Erilli,
Erol Eğrioğlu,
Ufuk Yolcu,
Çağdaş Hakan Aladağ,
Vedide Rezan Uslu
Publication year - 2010
Publication title -
doğuş üniversitesi dergisi
Language(s) - English
Resource type - Journals
eISSN - 1308-6979
pISSN - 1302-6739
DOI - 10.31671/dogus.2019.175
Subject(s) - computer science
Obtaining the inflation prediction is an important problem. Having this prediction accurately will lead to more accurate decisions. Various time series techniques have been used in the literature for inflation prediction. Recently, Artificial Neural Network (ANN) is being preferred in the time series prediction problem due to its flexible modeling capacity. Artificial neural network can be applied easily to any time series since it does not require prior conditions such as a linear or curved specific model pattern, stationary and normal distribution. In this study, the predictions have been obtained using the feed forward and recurrent artificial neural network for the Consumer Price Index (CPI). A new combined forecast has been proposed based on ANN in which the ANN model predictions employed in analysis were used as data.

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