Using Artificial Neural Networks To Forecast Gdp For Turkey

Karaatli, Meltem (2012) Using Artificial Neural Networks To Forecast Gdp For Turkey. In: 3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo.

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Abstract

Artificial Neural Networks (ANN) is a system resembling biological neural systems and uses working principles of human brain as a base. ANN can be applied in various fields for the purposes of forecasting, classification, optimization, data binding and so on. ANN has been frequently used in financial applications in recent years. In this study, ANN is used in forecasting Gross Domestic Product of Turkey. Gross Domestic Product (GDP) refers to the market value of all final goods and services produced within a country in a given period. GDP can be thought as the size of an economy and it is the foremost important measure of macroeconomic performance of a country, a country’s health and standard of living. Therefore, expectations about future GDP can be the primary determinant of investments, employment, wages, profits and even stock market activities. With respect to its economic significance mentioned above, the purpose of this study is to forecast Gross Domestic Product (GDP) for Turkey and to test the ability of ANN Method in forecasting GDP. Keywords: Importance of Gross Domestic Product, Forecasting, Artificial Neural Networks.

Item Type: Conference or Workshop Item (Paper)
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Faculty of Economics > Management Department
Depositing User: Users 173 not found.
Date Deposited: 17 Oct 2012 13:41
Last Modified: 17 Oct 2012 13:41
URI: http://eprints.ibu.edu.ba/id/eprint/1129

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