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Investment risks evaluation on high-tech projects based on analytic hierarchy process and BP neural network

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1 Author(s)
Jiang Hua ; School of Economics and Management, Hebei University of Engineering, Handan, China

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.

Published in:

2009 ISECS International Colloquium on Computing, Communication, Control, and Management  (Volume:1 )

Date of Conference:

8-9 Aug. 2009