Title :
Notice of Retraction
Predicting corporate financial distress based on RS-PCA-RBFN model
Author :
Zhu Shiwei ; Zhao Yanqing ; Yu Junfeng ; Wang Lei
Author_Institution :
Inf. Res. Inst., Shandong Acad. of Sci., Jinan, 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.
This paper is to propose a hybrid rough sets and PCA-RBFN model for corporate financial distress prediction in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, the RS is applied to reduce the indicator, and the PCA method is employed to select indicators, the RBFN is finally used as a predicting tool for corporate financial situation. In addition, to evaluate the performance of the proposed approach, we compare its results with those of BPN and conventional RBFN. The experimental results show that the proposed hybrid model outperforms the other methods.
Keywords :
financial management; principal component analysis; radial basis function networks; rough set theory; corporate financial distress; corporate financial situation; predicting tool; principle component analysis; radial basis function network; rough sets; Logistics; financial distress prediction; principle component analysis; radial basis function neural network; rough sets;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5563540
