Title :
Project financing risk assessment based on ACO and SVM
Author :
Jinyu, Tian ; Xin, Zhao
Author_Institution :
Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding, China
Abstract :
Based on the combination of ant colony optimization (ACO)and support vector machines (SVM) theory, the model of project financing risk assessment is established to recognizing the financing risk of project. By making use of ACO obtaining appropriate parameters we can improve the general recognizing ability of SVM. After that, these parameters are used to develop classification rules and train SVM. The effectiveness of our methodology was verified by experiments comparing BP neural networks with our approach.
Keywords :
financial management; optimisation; project management; risk management; support vector machines; ACO; BP neural network; SVM; ant colony optimization; financing risk recognition; project financing risk assessment; support vector machine theory; Ant colony optimization; Communication system control; Energy management; Financial management; Neural networks; Project management; Risk management; Support vector machine classification; Support vector machines; Training data; SVM; ant colony optimization; project financing; risk assessment;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5267657
