Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

被引：10

作者：

Kim, Sungki ^{[1
]}

Ko, Wonil ^{[1
]}

Nam, Hyoon ^{[1
]}

Kim, Chulmin ^{[2
]}

Chung, Yanghon ^{[3
]}

Bang, Sungsig ^{[3
]}

机构：

[1] Korea Atom Energy Res Inst, Nucl Fuel Cycle Anal, 1045 Daedeokdaero, Daejeon 305353, South Korea

[2] Korea Adv Inst Sci & Technol, Dept Nucl & Quantum Engn, 291 Daehak Ro, Daejeon 305701, South Korea

[3] Korea Adv Inst Sci & Technol, Dept Business & Technol Management, 291 Daehak Ro, Daejeon 305701, South Korea

来源：

NUCLEAR ENGINEERING AND TECHNOLOGY | 2017年 / 49卷 / 05期

关键词：

ARIMA Model; Cost Driver; Forecasting; Nuclear Fuel Cycle Cost; Uranium Price; SHALE GAS; FUTURE; ARIMA; CHINA;

D O I：

10.1016/j.net.2017.05.007

中图分类号：

TL [原子能技术]; O571 [原子核物理学];

学科分类号：

0827 ; 082701 ;

摘要：

This paper presents a method for forecasting future uranium prices that is used as input data to calculate the uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, the statistical autoregressive integrated moving average (ARIMA) model and existing engineering cost estimation method, the so-called escalation rate model, were subjected to a comparative analysis. When the uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting was calculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of error of 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model at decreasing uncertainty in nuclear fuel cycle cost calculation. (C) 2017 Korean Nuclear Society, Published by Elsevier Korea LLC.

引用

页码：1063 / 1070

页数：8

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