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Model of Viability Prediction Based on Neural Network and Data Mining Technique for Forest Industry Enterprise

机译:基于神经网络和数据挖掘技术的林业企业生存能力预测模型

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The operating status of a forest industry enterprise is disclosed periodically for viability. As a result, the manager usually only get information about the operating decision. An employer may be in after the formal financial statement has been published. If the employer executives intentionally package financial statements with the purpose of hiding the actual status of the forestry industry enterprise, then manager will have even less chance of obtaining the real financial information. To improve the accuracy of the viability prediction, viability ratios, non-viability ratios, and factor analysis had been used to extract adaptable variables. Moreover, the neural network and data mining technique were used to build the viability prediction model. The empirical experiment with a total of viability and nonviability ratios and projects as the initial samples obtained a satisfactory result, which testifies for the feasibility and validity of our proposed methods for the viability prediction of forestry industry enterprise.
机译:为了生存,定期披露林业企业的经营状况。结果,管理者通常仅获得有关操作决策的信息。正式财务报表发布后,雇主可能会加入。如果雇主高管有意打包财务报表以隐藏林业企业的实际状况,那么经理将获得真实财务信息的机会甚至更少。为了提高生存能力预测的准确性,已经使用生存率,非生存率和因子分析来提取适应性变量。此外,使用神经网络和数据挖掘技术来建立生存能力预测模型。以总生存力和非生存力比率以及项目作为初始样本的经验实验获得了令人满意的结果,证明了我们提出的林业企业生存能力预测方法的可行性和有效性。

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