Title :
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
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;
Conference_Titel :
Human System Interaction (HSI), 2013 The 6th International Conference on
Conference_Location :
Sopot
Print_ISBN :
978-1-4673-5635-0
DOI :
10.1109/HSI.2013.6577854
