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FORECASTING OF CHANGES OF COMPANIES FINANCIAL STANDINGS ON THE BASIS OF SELF-ORGANIZING MAPS

机译:在自组织地图的基础上预测公司财务销售的变化

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The multivariate discriminate models have been used in area of bankruptcy analysis for many years. In this paper we suggest to conjunct the principles of traditional discriminate bankruptcy models with modern methods of machine learning. We propose the forecasting model based on Self-organizing maps, where inputs are indicators of multivariate discriminate model. Accuracy of forecasting is improved via changing weights with supervised learning type ANN. We've presented results of testing of this model in various aspects.
机译:多元区分模型已被用于破产分析领域多年。在本文中,我们建议用现代的机器学习方法与传统的鉴别破产模型的原则相结合。我们提出了基于自组织地图的预测模型,其中输入是多元区分模型的指标。通过使用监督学习类型ANN的权重改善预测的准确性。我们在各个方面提出了对该模型的测试结果。

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