Economic classification and regression problems and neural networks

Arnošt Veselý
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Arnošt Veselý: Department of Information Engineering, Faculty of Economics and Management, Czech University of Life Sciences, Prague, Czech Republic

Agricultural Economics, 2011, vol. 57, issue 3, 150-157

Abstract: Artificial neural networks provide powerful models for solving many economic classifications, as well as regression problems. For example, they were successfully used for the discrimination between healthy economic agents and those prone to bankruptcy, for the inflation-deflation forecasting, for the currency exchange rates prediction, or for the prediction of share prices. At present, the neural models are part of the majority of standard statistical software packages. This paper discusses the basic principles, which the neural network models are based on, and sum up the important principles that must be respected in order that their utilization in practice is efficient.

Keywords: multilayer neural networks; classification; bankruptcy prediction; time series prediction; neural network training; error functions (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:57:y:2011:i:3:id:50-2010-agricecon

DOI: 10.17221/50/2010-AGRICECON

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