Title :
The Application of Artificial Neural Networks in Risk Assessment on High-Tech Project Investment
Author_Institution :
Sch. of Econ. & Manage., Hebei Univ. of Eng., Handan, China
Abstract :
Investment risks assessment of high-tech projects is a more complex process, involving various factors and it is not entirely the linear relationship between influencing factors and measurement results. Artificial neural network (ANN) has a strong nonlinear mapping ability, with strong learning ability and high classification and prediction accuracy. The paper applied ANN to establish a new risk assessment model of high-tech project investment and used MATLAB software to carry out example simulations respectively with BP neural network model and RBF neural network model. The results showed that it is effective to apply ANN to assess the high-tech project investment risk and RBF network is more suitable than BP network.
Keywords :
backpropagation; investment; mathematics computing; radial basis function networks; risk management; BP neural network model; MATLAB software; RBF neural network; artificial neural networks; high-tech project investment; nonlinear mapping ability; risk assessment; strong learning ability; Artificial neural networks; Investments; Macroeconomics; Mathematical model; Neural networks; Project management; Radial basis function networks; Research and development; Risk analysis; Risk management; BP neural network; RBF neural network; high-tech projects; investment risk assessment;
Conference_Titel :
Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3705-4
DOI :
10.1109/BIFE.2009.13
