一种改进投影寻踪风险评估函数模型

doi:10.3969/j.issn.0255-8297.2019.01.011

Abstract

Abstract:

A model of project pursuit risk assessment is developed based on information entropy theory for dealing with the weakness of current project pursuit model. First, range normalization is performed to remove dimensional effect and keep the same trend for indicators. Second, the entropy of the projection value, which cannot describe sequence variations under some situations quantitatively, is applied to express the projection index function, and the optimal projection direction is estimated by the maximum entropy principle for dimension reduction. Finally, an S type risk assessment model is built and it characterized from the aspects of monotonicity, boundness, and continuous and smooth change. Two experiments about flood risk and marine environmental risk have been made. The results show that our model can improve the result of the project pursuit by between 7.0% and 8.8% for the flood risk, and have an evident improvement by between 27.1% and 53.9% for the marine environmental risk.

Key words: entropy, projection index function, maximum entropy principle, the best projection direction, S type function

CLC Number:

TV213

QIAN Long-xia, ZHANG Ren, WANG Hong-rui, HOU Tai-ping. An Improved Project Pursuit Risk Assessment Function Model[J]. Journal of Applied Sciences, 2019, 37(1): 112-125.

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An Improved Project Pursuit Risk Assessment Function Model

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