DocumentCode :
2227374
Title :
An Approach of Enterprise Financial Crisis Pre-warning Based on Multi-class Support Vector Machine
Author :
Song, Jiekun ; Zhang, Yu
Author_Institution :
Sch. of Econ. & Manage., China Univ. of Pet. (East China), Dongying, China
Volume :
3
fYear :
2010
fDate :
26-28 Nov. 2010
Firstpage :
517
Lastpage :
520
Abstract :
An approach based on multi-class support vector machine (SVM) is put forward for pre-warning enterprise financial crisis. On the basis of financial crisis pre-warning index system, the actual situations of enterprises´ financial crisis are used as learning samples to train and test the learning machine through cross-validation and one to one vote methods and all the optimal hyper plane functions of every two classes can be obtained. An example testifies the efficiency and feasibility of the model, which provides a new way for dynamic pre-warning of enterprise financial crisis.
Keywords :
enterprise resource planning; financial management; learning (artificial intelligence); support vector machines; enterprise financial crisis prewarning; learning machine; learning sample; multiclass support vector machine; optimal hyper plane function; prewarning index system; financial crisis; multi-class; pre-warning; support vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2010 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-8829-2
Type :
conf
DOI :
10.1109/ICIII.2010.445
Filename :
5694790
Link To Document :
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