DocumentCode :
3024228
Title :
An Application of Fuzzy Cognitive Map Based on Active Hebbian Learning Algorithm in Credit Risk Evaluation of Listed Companies
Author :
Zhai, Dong-Sheng ; Ya-Nan Chang ; Zhang, Juan
Author_Institution :
Dept. of Manage. Sci. & Eng., Beijing Univ. of Technol., Beijing, China
Volume :
4
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
89
Lastpage :
93
Abstract :
This paper suggests using FCM to investigate the problem of credit risk evaluation of listed companies by referring to some domestic and abroad researches of fuzzy cognitive map and credit risk. Firstly, the present research status of FCM is briefly introduced. Then, this paper completely studies the basis theory and inner inference mechanism of FCM, and the Active Hebbian Learning (AHL) algorithms of it are especially described. Finally, this paper studies how to model and simulate the problem of credit risk evaluation of listed companies using FCM. The first section of this part analyzes the factors that affect the level of credit risk of listed companies; then, the next section studies how to construct the FCM of credit risk evaluation of listed companies based on qualitative consideration. In the end, the developed FCM model is tested by applying the AHL algorithm based on 96 samples, and we justified the effectiveness of the FCM model for evaluating credit risk level of listed companies.
Keywords :
Hebbian learning; finance; fuzzy reasoning; fuzzy set theory; risk analysis; FCM; active Hebbian learning algorithm; credit risk evaluation; fuzzy cognitive map; inner inference mechanism; listed companies; Artificial intelligence; Computational intelligence; Conference management; Decision making; Engineering management; Fuzzy cognitive maps; Hebbian theory; Paper technology; Risk management; Technology management; Active Hebbian Learning; Credit Risk Evaluation; Fuzzy Cognitive Map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.214
Filename :
5376426
Link To Document :
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