The Risk Assessment of High-Tech Project Based on Comprehensive Evaluation of Fuzzy and Gray Model

Abstract:

High-tech projects have high risks involving wide range of links, high expense of investment, long period of development and production cycle, complicated operation system, etc. When evaluating the project's risk, a separate gray method or fuzzy theory model is not comprehensive, it should combine the gray method with the fuzzy evaluation model. From the fuzzy evaluation and gray evaluation method the gray clustering statistic could be obtained by use of grey cluster theory. It is necessary to construct fuzzy membership matrix of risk and establish a fuzzy and gray comprehensive evaluation method, and adequately adopt expert's evaluation information of the fuzziness and grayness. Finally, using concrete empirical analysis in aviation armament project risk assessment, the feasibility and the correctness of the model are verified.

• Periodical: Applied Mechanics and Materials (Volumes 475-476)
• Pages: 1734-1737
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.475-476.1734
• Online since: December 2013
• Authors: Xiao Bin Ding*
• Keywords: AHP, Comprehensive Evaluation, Fuzzy and Gray Model, High-Tech

References

[1] De-mian Chen, The theory and method of high technology investment risk prediction and assessment, Prediction. vol. 1, 1998, pp.48-50.

[2] Xu-song Xu, Fuzzy comprehensive evaluation model of investment risk of high tech projects, Quantitative and technical economic research. vol. 1, 2000, pp.34-36.

[3] Xin-hong Zhang, A Neural Network Synthetic Evaluation Method for the Investing Risk of the High-Technical Projects, Intelligence Science Report. Vol. 20, No. 5, October, 2001, pp.608-611.

[4] You-jie Lu. Project Management, Chinese investment and construction . vol. 1, (1997).

[5] OECD, Classification of High-Technology Products and Industries, Party No. 9 of the Industry Committee on Industrial Statistics, (94)11, Paris, September, 1994, 19-21.

[6] Vito F. Uricchio, Raffaele Giordano. A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation[J]. Journal of Environmental Management 73 (2004): 189-197.

DOI: 10.1016/j.jenvman.2004.06.011

[7] K. R. Suresh. A fuzzy risk approach for performance evaluation of an irrigation reservoir system[J]. Agricultural Water Management, 2004, 69, (3): 159-177.

DOI: 10.1016/j.agwat.2004.05.001

[8] Yo-Ping Huang, Sheng Fang Wang. Designing a fuzzy model by adaptive macroevolution genetic algorithms[J]. Fuzzy Sets and Systems2000, (113): 367-379.

DOI: 10.1016/s0165-0114(98)00193-6

[9] Hsin-Hsi Lai. Form design of product image using grey relational analysis and neural network models[J] . Computers & operations Research, 2004(25): 1-23.

DOI: 10.1016/j.cor.2004.03.021

[10] S.P. Lo., The Application of an ANFIS and Grey System Method in Turning Tool-Failure Detection [J]. The international journal of advanced manufacturing Technology. 2002(19): 564-572.

DOI: 10.1007/s001700200061