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Analyzing economic structure and comparing the results of the predicted economic growth based on linear and non-linear models

机译:分析经济结构,并基于线性和非线性模型比较预测的经济增长结果

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Investigating the effectivefactors on economic growth is of great importance for most economists. Although, lots of studies have been done on economic growth in the world, it has less been regarded in Iran. In this article, by estimating growth regression, we attempt to investigate the supply side of economic growth in Iran. Then a comparison was done between the predictive results of Neural network (NN) and Slow models. Also by comparing the predictive results of models for the average percentage of annual growth, it is predicted that the average percentage of solow and neural-network models are 7.17 and 5.92% for 2002 to 2006, respectively. Evaluation of results from the models on the basis of criteria shows that Neural-networkmodelpredicts better than Solow model. In other words, forecasting by the model neural-network is recommended.
机译:对于大多数经济学家来说,研究影响经济增长的有效因素非常重要。尽管已经对世界经济增长进行了大量研究,但在伊朗却很少有人考虑。在本文中,通过估算增长回归,我们尝试调查伊朗经济增长的供给方。然后比较了神经网络(NN)和Slow模型的预测结果。通过比较模型对年平均增长率的预测结果,可以预测2002年至2006年solow模型和神经网络模型的平均百分比分别为7.17%和5.92%。基于标准对模型结果的评估表明,神经网络模型的预测优于Solow模型。换句话说,建议使用模型神经网络进行预测。

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