Department of Informática, University of Vigo, Edificio Politécnico, Campus Universitario As Lagoas s/n, Ourense, 32004, Spain.
Int J Neural Syst. 2011 Aug;21(4):277-96. doi: 10.1142/S0129065711002833.
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.
在过去的几年中，人们越来越需要开发创新的工具，以帮助中小企业预测业务失败和金融危机。在本研究中，我们提出了一种新颖的混合智能系统，旨在监测公司的运营模式并预测可能的失败。该系统通过基于神经网络的多代理系统实现，该系统将公司的不同参与者建模为代理。多代理系统的核心是一种代理，它包含基于案例的推理系统，并自动化业务控制过程和失败预测。基于案例的推理系统的阶段通过 Web 服务实现：检索阶段使用基于自组织映射集合的创新加权投票汇总方法，重用阶段通过径向基函数神经网络实现。开发了一个初始原型，并展示了在实际场景中针对中小企业获得的结果。
