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Coupled Model of Artificial Neural Network and Grey Model for Tendency Prediction of Labor Turnover

机译：人工神经网络与灰色模型的耦合预测

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摘要

The tendency of labor turnover in the Chinese enterprise shows the characteristics of seasonal fluctuations and irregular distribution of various factors, especially the Chinese traditional social and cultural characteristics. In this paper, we present a coupled model for the tendency prediction of labor turnover. In the model, a time series of tendency prediction of labor turnover was expressed as trend item and its random item. Trend item of tendency prediction of labor turnover is predicted using Grey theory. Random item of trend item is calculated by artificial neural network model (ANN). A case study is presented by the data of 24 months in a Chinese matured enterprise. The model uses the advantages of "accumulative generation" of a Grey prediction method, which weakens the original sequence of random disturbance factors and increases the regularity of data. It also takes full advantage of the ANN model approximation performance, which has a capacity to solve economic problems rapidly, describes the nonlinear relationship easily, and avoids the defects of Grey theory.
机译：中国企业的劳动力流动趋势表现出季节性波动和各种因素的不规则分布的特征，尤其是中国传统的社会文化特征。在本文中，我们提出了一种用于预测劳动力流动趋势的耦合模型。在模型中，将劳动力流动趋势预测的时间序列表示为趋势项及其随机项。用灰色理论对劳动力流动趋势预测的趋势项进行预测。趋势项的随机项是通过人工神经网络模型（ANN）计算的。一个中国成熟企业的24个月数据提供了一个案例研究。该模型利用了Gray预测方法的“累积生成”优势，从而削弱了随机干扰因子的原始序列并增加了数据的规律性。它还充分利用了ANN模型的逼近性能，它具有快速解决经济问题的能力，易于描述非线性关系，并且避免了Gray理论的缺陷。

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  • 来源
    《Mathematical Problems in Engineering》 |2014年第8期|918307.1-918307.6|共6页
  • 作者

    Yueru Ma; Lijun Peng;

  • 作者单位

    Business School, Central South University, Changsha, Hunan 410083, China;

    Business School, Central South University, Changsha, Hunan 410083, China;

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