Title :
Investment risks evaluation on high-tech projects based on analytic hierarchy process and BP neural network
Author_Institution :
Sch. of Econ. & Manage., Hebei Univ. of Eng., Handan, China
Abstract :
In view of the existing problems of investment risks evaluation on high-tech industry projects such as a lack of systematic, with too much subjectivity and from the point to improve evaluation efficiency and effectiveness, the paper combined analytic hierarchy process (AHP) with BP neural network to establish a new and suitable risk evaluation model of high-tech projects. Firstly, we applied AHP to construct a comprehensive risk evaluation index system and screened the evaluation indexes according to their weights. On this basis, using MATLAB software with BP neural network model, we carried out example simulations and results were analyzed. The results showed that the combination model of analytic hierarchy process with BP neural network model (AHP-BPNN) is effective.
Keywords :
backpropagation; neural nets; risk management; BP neural network; analytic hierarchy process; evaluation indexes; investment risks evaluation; Communication system control; Computer network management; Computer networks; Engineering management; Investments; Mathematical model; Neural networks; Project management; Risk analysis; Risk management; BP neural network; analytic hierarchy process; high-tech projects; investment risks evaluation;
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.2009.5268119
