...
首页> 外文期刊>Neural computing & applications >Forecasting classification of operating performance of enterprises by ZSCORE combining ANFIS and genetic algorithm
【24h】

Forecasting classification of operating performance of enterprises by ZSCORE combining ANFIS and genetic algorithm

机译:结合ANFIS和遗传算法的ZSCORE预测企业经营绩效分类。

获取原文
获取原文并翻译 | 示例

摘要

Classification of operating performance of the enterprises is not only a hot issue emphasized by the management, but it is an important reference for investors too in their decision-making. Generally speaking, when predicting or analyzing business performance classification, most researchers adopt corporate financial early warning or credit-rating models, which pretty much use previous data and facts. Therefore, this paper brings about an alternative method to discriminate between excellent and poor business management, so as to take preventive measures prior to business crisis or bankruptcy. We collected the financial reports and financial ratios from the listed firms in mainland China and Taiwan as our samples to build up four kinds of forecasting models for business performance. The empirical results show that the hybrid model provides better classification forecasting capability than the other models, while the ANFIS model adjusted by genetic algorithm could effectively enhance the classification forecasting capability.
机译:企业经营绩效的分类不仅是管理层强调的热点问题,也是投资者决策的重要参考。一般来说,在预测或分析业务绩效分类时,大多数研究人员会采用公司财务预警或信用评级模型,这些模型几乎都使用以前的数据和事实。因此,本文提出了另一种方法来区分优秀和较差的业务管理,以便在业务危机或破产之前采取预防措施。我们收集了中国大陆和台湾上市公司的财务报告和财务比率作为样本,建立了四种业务绩效预测模型。实证结果表明,混合模型提供了比其他模型更好的分类预测能力,而遗传算法调整后的ANFIS模型可以有效地提高分类预测能力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号