Prediction of Nuclear Power Project Cost Based on Improved Non-Equidistant GM (1,1) Model and Exponential Regression Model

Bing Yi Liu; Dong Xiao Niu; Jin Peng Qiu; Hui Xu; Yue Wang

doi:10.4028/www.scientific.net/AMM.644-650.3489

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Application of On-Line Ultrasonic and UHF Partial Discharge Detection in 1000kV GIS
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Prediction of Nuclear Power Project Cost Based on...

Prediction of Nuclear Power Project Cost Based on Improved Non-Equidistant GM (1,1) Model and Exponential Regression Model

Abstract:

Today, faced with the problem of international energy supply difficulties, due to the nuclear power’s fewer of its resources consumption, little environmental pollution and other advantages, it has become one of the essential pillars of the electricity supply. This paper analyzed from a comprehensive localization of nuclear power plants, then use the non-equidistant GM (1,1) model and the exponential regression model to predict the construction cost of nuclear power, and do the error analysis. The conclusion that by increasing the degree of localization of domestic nuclear power construction, which can effectively reduce the cost of building nuclear power plants conclusions.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

3489-3492

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.3489

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Online since:

September 2014

Authors:

Bing Yi Liu, Dong Xiao Niu, Jin Peng Qiu, Hui Xu, Yue Wang

Keywords:

Exponential Regression, GM(1,1), Localization, Nuclear

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