DocumentCode
1860316
Title
Notice of Retraction
Coal Mine Enterprises Merger & Acquisition Efficiency Prediction Based on Support Vector Machine
Author
Chen Xiang ; Cai Weihua
Author_Institution
Inst. of Econ. & Manage., Hebei Univ. of Eng., Handan, China
fYear
2010
fDate
9-10 Jan. 2010
Firstpage
564
Lastpage
567
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.
Presently, China coal mine enterprises are under merger and reorganization great environment. These enterprises merger and acquisition (M&A) process efficiency predictions lack theoretical support. The paper constructed coal enterprises M&A efficiency evaluation system, built the M&A efficiency prediction model based on support vector machine (SVM). The paper investigated the data in 2004-2008 of coal enterprises M&A, applying the model made empirical analysis. The results show the method is feasible and effective.
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.
Presently, China coal mine enterprises are under merger and reorganization great environment. These enterprises merger and acquisition (M&A) process efficiency predictions lack theoretical support. The paper constructed coal enterprises M&A efficiency evaluation system, built the M&A efficiency prediction model based on support vector machine (SVM). The paper investigated the data in 2004-2008 of coal enterprises M&A, applying the model made empirical analysis. The results show the method is feasible and effective.
Keywords
coal; corporate acquisitions; financial management; mining industry; support vector machines; China coal mine enterprises; M&A efficiency evaluation system; merger and acquisition process efficiency predictions; support vector machine; Artificial neural networks; Corporate acquisitions; Data mining; Economic forecasting; Electronic mail; Engineering management; Environmental economics; Marketing and sales; Predictive models; Support vector machines; SVM; coal enterprises M&A; efficiency prediction; index system;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location
Phuket
Print_ISBN
978-1-4244-5397-9
Type
conf
DOI
10.1109/WKDD.2010.74
Filename
5432489
Link To Document