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Mathematical Problems in Engineering
Volume 2014, Article ID 918307, 6 pages
http://dx.doi.org/10.1155/2014/918307
Research Article

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

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

Received 20 December 2013; Revised 9 March 2014; Accepted 11 March 2014; Published 15 April 2014

Academic Editor: Gongnan Xie

Copyright © 2014 Yueru Ma and Lijun Peng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.