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A Comparative Approximate Economic Behavior Analysis of Support Vector Machines and Neural Networks Models


  • Amin Gharipour

    (Mathematical Science Dep., University of Isfahan, of Technology, Isfahan, Iran)

  • Morteza Sameti

    (Economic Dep., University of Isfahan, Iran)

  • Ali Yousefian

    (Mathematical Science Dep., Isfahan University of Technology, Isfahan, Iran)


The application of the artificial neural networks in economics and business goes back to 1950s, while the main part of the applications has been developed in more recent years. Reviewing this research indicates that the development and applications of neural network are not limited to a specific application area as it spans a wide variety of fields from prediction to classification, as most of the applications in economics primarily focus on the predictive power of the neural networks. Many researches using statistical and Neural Networks (NNs) models in economics but few involved support vector machines in their studies. In this paper for the first time we compare the approximate economic behavior ability of artificial neural networks (ANN) and support vector machines using a set of data on some Middle East countries.

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  • Amin Gharipour & Morteza Sameti & Ali Yousefian, 2010. "A Comparative Approximate Economic Behavior Analysis of Support Vector Machines and Neural Networks Models," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 15(2), pages 17-40, spring.
  • Handle: RePEc:eut:journl:v:15:y:2010:i:2:p:17

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    References listed on IDEAS

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    1. Mostafaei, Kamran & maleki, Shaho & Zamani Ahmad Mahmoudi, Mohammad & Knez, Dariusz, 2022. "Risk management prediction of mining and industrial projects by support vector machine," Resources Policy, Elsevier, vol. 78(C).

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