期刊名称：International Journal of Economics & Management Sciences
电子版ISSN：2162-6359
出版年度：2015
卷号：4
期号：6
页码：1-5
DOI：10.4172/2162-6359.1000254
语种：English
出版社：OMICS International
摘要：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 modeling 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.
