Title :
Notice of Retraction
A prediction research on the scale of operation and management talent of China´s coal industry during “12th Five-Year plan” period
Author :
Kai Tan ; Xia Peng
Author_Institution :
Sch. of Sci., China Univ. of Min. & Technol., Beijing, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we make a dynamic correlation analysis of the development and change of the total demand and the relevant factors of operation and management talent in China´s coal industry through the correlated data investigation of 30 large and medium-sized state-owned key colliery, by using the mixed methods of factor analysis, multiple linear regression and grey model, predict its total demand in “12th Five-Year plan” period, provide a theoretical basis and reference for the development of human resources, training and management in coal industry.
Keywords :
coal; correlation methods; grey systems; human resource management; industrial training; mining industry; regression analysis; supply and demand; 12th five-year plan; China coal industry; dynamic correlation analysis; factor analysis; grey model; human resource development; management talent; medium-sized state-owned key colliery; multiple linear regression; prediction research; total demand; Coal; Coal industry; Linear regression; Mathematical model; Predictive models; Production; Remuneration; coal industry; factor analysis; grey model; multiple linear regression; operation and management talent;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Dengleng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6011389
