Economic Analysis of Risky Projects Based on LS-SVM
Xin Chen Guo, Chao Zhang, Fu Wei Zhang · Applied Mechanics and Materials · 2011
Risk management and its accurate analysis are very important for project management. RBF and MLP Neural Network Model are common methods of risk management and analysis, which are not accurate enough. In this paper a new method based on LS-SVM is introduced. Analytical models of risky projects are investigated and function approximation results are compared. Experimental results show that the regression analysis of risk based on LS-SVM method has higher prediction accuracy and better generalization ability.