All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.


Research of risk assessment and prediction based on support vector machine

Author(s): Dakai Li, Yu Li, Zhang Qi-Wen

Building a suitable credit risk evaluation model is very important, that is because loan business is one of the most important assets of commercial Banks. In this paper, we introduce a kind of learning algorithm which contains small sample learning and construct a new method which is called support vector machine (SVM). SVM is developed based on a new theory that is popular used in the field of intelligent learning system in recent years. The credit risk assessment model of commercial bank is established finally. By multiple discriminate analyses and the comparison of neural network model, confirms the validity and superiority of the method when be used in risk assessment.

Share this       

Share this Page.

Table of Contents

Scimago Journal Rank

izmir escort izmir escort bursa escort antalya escort izmir escort porno porno izle türk porno eskişehir escort bartın escort burdur escort havalandırma izmir escort bursa escort porno indir izle escort izmir