Profiieseeker — Early warning system for predicting economic situation of small and medium enterprises

Author

Burda, Andrzej ; Cudek, P. ; Hippe, Z.S.

Author_Institution

Univ. of Manage. & Adm., Zamość, Poland

fYear

2013

fDate

6-8 June 2013

Firstpage

398

Lastpage

400

Abstract

This paper presents the construction of the ProfileSEEKER the information system for early warning small and medium-sized enterprises from bankruptcy. The developed system is a set of five classifiers, using a variety of topologies of artificial neural networks and Bayes belief network, supported by supervised machine learning methods. System performance was evaluated using the original validation, called queue validation procedure.

Keywords

bank data processing; economics; learning (artificial intelligence); management information systems; neural nets; small-to-medium enterprises; Bayes belief network; ProfileSEEKER; artificial neural networks; bankruptcy; early warning system; economic situation prediction; information system; queue validation procedure; small and medium enterprises; supervised machine learning methods; Artificial neural networks; Biological system modeling; Companies; Data models; Economics; Predictive models; artificial neural networks; machine learning; predicting economic situation SMEs; queue validation;

fLanguage

English

Publisher

ieee

Conference_Titel

Human System Interaction (HSI), 2013 The 6th International Conference on

Conference_Location

Sopot

ISSN

2158-2246

Print_ISBN

978-1-4673-5635-0

Type

conf

DOI

10.1109/HSI.2013.6577854

Filename

6577854