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引用次数: 3

摘要

企业的诸多因素在激烈的商业竞争中发挥着重要作用。有些是积极的,有些是消极的。如果正确处理这些因素,就会发现潜在的危机,避免失败,甚至破产。设计一个危机预测系统是必要的。一个好的预测不仅可以预测到危机并采取控制措施,而且可以为顺利应对危机提供足够的准备和计划。这些因素是要分析的基础数据,以支持这样一个系统,可能是定量的,也可能是定性的。为了解决企业危机预测系统中数据分析存在的半结构化和非结构化问题,提出了一种基于离群数据挖掘的企业危机预测系统。阐述了系统的组织结构、框架结构、功能和工作原理。并以欺骗预测为例说明了其工作过程。实验结果表明,该方法是有效的,在预测领域具有广泛的应用前景。
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An enterprise crisis predicting system based on outlier data mining
Many factors in an enterprise are playing important roles in intense commercial competitions. Some are positive and some are negative. If dealing with these factors correctly, potential crisis will be found to avoid defeats, even bankrupt. Designing a crisis predicting system is necessary. An excellent predicting can not only predict expecting crisis and take controlling measures, but also can provide enough preparation and plan to deal with crisis smoothly. The factors are the basis data to be analyzed to support such a system and maybe they are quantitative or qualitative. In order to solve such problems as half-structured and non-structured data analysis in enterprise crisis predicting system, a predicting system based on outlier data mining is put forward. The system organization, frame construction, function and working principles are illustrated. And the working process is showed by an example of cheat predicting. The experimental results show that this method is efficient and it has wide utilization in predicting fields.
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