Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost |
Kim, Sungki
(Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute)
Ko, Wonil (Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute) Nam, Hyoon (Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute) Kim, Chulmin (Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology) Chung, Yanghon (Department of Business and Technology Management, Korea Advanced Institute of Science and Technology) Bang, Sungsig (Department of Business and Technology Management, Korea Advanced Institute of Science and Technology) |
1 | K. Taneja, S. Ahmad, K. Ahmad, S.D. Attri, Time series analysis of aerosol optical depth over New Delhi using Box-Jenkins ARIMA modeling approach, Atmos. Pollut. Res. 7 (2016) 1-12. DOI |
2 | C. Yuan, S. Liu, Z. Fang, Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM (1, 1) model, Energy 100 (2016) 384-390. DOI |
3 | K. Kandananond, Forecasting electricity demand in Thailand with an artificial neural network approach, Energies 4 (2011) 1246-1257. DOI |
4 | J.A. Scott, Skills & Knowledge of Cost Engineering- Appendix E3, AACE International Press, Morgantown (WV), 2004. |
5 | Organization for Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA), The Economics of the Back-end of the Nuclear Fuel Cycle, OECD/NEA, Paris, France, 2013. |
6 | B.K. Sovacool, Cornucopia or curse? Reviewing the costs and benefits of shale gas hydraulic fracturing (fracking), Renew. Sust. Energ. Rev. 37 (2014) 249-264. DOI |
7 | R. Middleton, H. Viswanathan, R. Currier, R. Gupta, as a fracturing fluid: potential for commercial-scale shale gas production and sequestration, Energy Procedia 63 (2014) 7780-7784. DOI |
8 | MIT, The Future of the Nuclear Fuel Cycle, Massachusetts Institute of Technology, Cambridge (MA), 2011. |
9 | L. Xia, D. Luo, J. Yuan, Exploring the future of shale gas in China from an economic perspective based on pilot areas in the Sichuan basin-A scenario analysis, J. Nat. Gas. Sci. Eng. 22 (2015) 670-678. DOI |
10 | S. Kim, W. Ko, S. Bang, Analysis of unit process cost for an engineering-scale pyroprocess facility using a process costing method in Korea, Energies 8 (2015) 8775-8797. DOI |
11 | S.K. Kim, W.I. Ko, Y.H. Lee, Development and validation of a nuclear fuel cycle analysis tool: a future code, Nucl. Eng. Technol. 45 (2013) 665-674. DOI |
12 | D.E. Shropshire, K.A. Williams, W.B. Boore, J.D. Smith, B.W. Dixon, M. Dunzik- Gougar, R.D. Adams, D. Gombert, Advanced Fuel Cycle Cost Basis, Idaho National Laboratory (INL), Idaho Falls (ID), 2007. |
13 | J.D. Park, Fundamental Cost Management Accounting, Hyungseul Press, Daegu, 2005. |
14 | S.J. Kang, The Theory of Cost Estimation, Dunam Press, Seoul, 2010. |
15 | H.G. Shin, Intermediate Accounting, Tamjin Press, Seoul, 2005. |
16 | G. Box, G. Jenkins, Time Series Analysis: Forecasting and Control, Holden Day, San Francisco (CA), 1970. |
17 | D.B. Jeong, Demand Forecasting of Time Series I, Hannarae Publishing, Seoul, 2009. |
18 | H.J. No, Well-defined Time Series Analysis Utilizing SPSS/Excel, YSWPUB, Paju, 2010. |
19 | W.H. Greene, Econometric Analysis, Pearson Education, (NJ), 2003. |
20 | F.S. Lasheras, F.J. de Cos Juez, A.S. Sanchez, A. Krzemien, P.R. Fernandez, Forecasting the COMEX copper spot price by means of neural networks and ARIMA models, Resour. Policy 45 (2015) 37-43. DOI |
21 | P. Ramos, N. Santos, R. Rebelo, Performance of state space and ARIMA models for consumer retail sales forecasting, Robot. Comput.-Integr. Manuf. 34 (2015) 151-163. DOI |