Coal mine enterprises merger and acquisition prediction based on wavelet neural network

Author

Yuncai Ning ; Xiang Chen

Author_Institution

Inst. of Manage., China Univ. of Min.&Technol., Beijing, China

Volume

1

fYear

2009

fDate

28-29 Nov. 2009

Firstpage

304

Lastpage

308

Abstract

Under present merger and reorganization great environment, the merger and acquisition (M&A) results of many China coal enterprises are ineffective. The predictions of coal enterprises M&A efficiency lack related theories support. The paper constructed a coal enterprises M&A efficiency assessment system, built a M&A efficiency prediction model based on wavelet neural network. It investigated the data in 2004-2008 of coal enterprises M&A, applying the model empirically analyzed the coal enterprises M&A efficiency, which results showed the prediction method is feasible and effective.

Keywords

corporate acquisitions; mining industry; neural nets; wavelet transforms; coal mine enterprises; enterprise acquisition prediction; enterprise merger prediction; wavelet neural network; Artificial neural networks; Computer network management; Conference management; Corporate acquisitions; Demand forecasting; Environmental management; Function approximation; Neural networks; Prediction methods; Predictive models; efficiency prediction; index system; merger and acquisition; wavelet neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4606-3

Type

conf

DOI

10.1109/PACIIA.2009.5406432

Filename

5406432