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Medientyp:
E-Artikel
Titel:
HYBRID NEURAL INTELLIGENT SYSTEM TO PREDICT BUSINESS FAILURE IN SMALL-TO-MEDIUM-SIZE ENTERPRISES
Beteiligte:
BORRAJO, M. LOURDES;
BARUQUE, BRUNO;
CORCHADO, EMILIO;
BAJO, JAVIER;
CORCHADO, JUAN M.
Erschienen:
World Scientific Pub Co Pte Lt, 2011
Erschienen in:International Journal of Neural Systems
Sprache:
Englisch
DOI:
10.1142/s0129065711002833
ISSN:
0129-0657;
1793-6462
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p>During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.</jats:p>