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DESIGNING A FORECAST MODEL FOR ECONOMIC GROWTH OF JAPAN USING COMPETITIVE (HYBRID ANN VS MULTIPLE REGRESSION) MODELS

Ecoforum Journal

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Title DESIGNING A FORECAST MODEL FOR ECONOMIC GROWTH OF JAPAN USING COMPETITIVE (HYBRID ANN VS MULTIPLE REGRESSION) MODELS
 
Creator DEMIR, Ahmet; Ishik University, Erbil, Iraq
SHADMANOV, Atabek; Ishik University, Erbil
AYDINLI, Cumhur; Ipek University, Ankara
ERAY, Okan; International Black Sea University, Tbilisi
 
Subject Artificial Neural Network; Hybrid Model; GDP Growth of Japan; Modelling Forecast; Variable Determination
E00
 
Description Artificial neural network models have been already used on many different fields successfully. However, many researches show that ANN models provide better optimum results than other competitive models in most of the researches. But does it provide optimum solutions in case ANN is proposed as hybrid model? The answer of this question is given in this research by using these models on modelling a forecast for GDP growth of Japan. Multiple regression models utilized as competitive models versus hybrid ANN (ANN + multiple regression models). Results have shown that hybrid model gives better responds than multiple regression models. However, variables, which were significantly affecting GDP growth, were determined and some of the variables, which were assumed to be affecting GDP growth of Japan, were eliminated statistically.
 
Publisher Association of Educational and Cultural Cooperation Suceava from Stefan cel Mare Universit
 
Date 2015-07-20
 
Format application/pdf
 
Identifier http://www.ecoforumjournal.ro/index.php/eco/article/view/174
 
Source Ecoforum Journal; Vol 4, No 2 (2015)
 
Language en
 
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