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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.1
- 수록면
- 1,063 - 1,070 (8page)
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This paper presents a method for forecasting future uranium prices that is used as input data to calculatethe uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, thestatistical autoregressive integrated moving average (ARIMA) model and existing engineering costestimation method, the so-called escalation rate model, were subjected to a comparative analysis. Whenthe uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting wascalculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of errorof 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model atdecreasing uncertainty in nuclear fuel cycle cost calculation
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참고문헌 (21)
참고문헌 신청
B. K. Sovacool / 2014 / Cornucopia or curse? Reviewing the costs and benefits of shale gas hydraulic fracturing (fracking) / Renew. Sust. Energ. Rev 37 : 249 ~ 264
C. Yuan / 2016 / Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average)model and GM (1, 1) model / Energy
D. B. Jeong / 2009 / Demand Forecasting of Time Series I / Hannarae Publishing
D. E. Shropshire / 2007 / Advanced Fuel Cycle Cost Basis
F. S. Lasheras / 2015 / Forecasting the COMEX copper spot price by means of neural networks and ARIMA models / Resour. Policy 45 : 37 ~ 43
C. Yuan / 2016 / Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average)model and GM (1, 1) model / Energy
D. B. Jeong / 2009 / Demand Forecasting of Time Series I / Hannarae Publishing
D. E. Shropshire / 2007 / Advanced Fuel Cycle Cost Basis
F. S. Lasheras / 2015 / Forecasting the COMEX copper spot price by means of neural networks and ARIMA models / Resour. Policy 45 : 37 ~ 43
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