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• W1980975236 abstract "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." @default.
• W1980975236 created "2016-06-24" @default.
• W1980975236 creator A5029807663 @default.
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• W1980975236 date "2011-08-01" @default.
• W1980975236 modified "2023-10-02" @default.
• W1980975236 title "HYBRID NEURAL INTELLIGENT SYSTEM TO PREDICT BUSINESS FAILURE IN SMALL-TO-MEDIUM-SIZE ENTERPRISES" @default.
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• W1980975236 doi "https://doi.org/10.1142/s0129065711002833" @default.
• W1980975236 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/21809475" @default.
• W1980975236 hasPublicationYear "2011" @default.
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