Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition
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DOI: 10.1007/s11269-015-0962-6
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- Jianhua Xu & Yaning Chen & Weihong Li & Qin Nie & Chunan Song & Chunmeng Wei, 2014. "Integrating Wavelet Analysis and BPANN to Simulate the Annual Runoff With Regional Climate Change: A Case Study of Yarkand River, Northwest China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2523-2537, July.
- Guo, Zhenhai & Zhao, Weigang & Lu, Haiyan & Wang, Jianzhou, 2012. "Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model," Renewable Energy, Elsevier, vol. 37(1), pages 241-249.
- Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
- Mustafa Turan & Mehmet Yurdusev, 2014. "Predicting Monthly River Flows by Genetic Fuzzy Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4685-4697, October.
- Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
- Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996.
"Efficient Tests for an Autoregressive Unit Root,"
Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
- Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "GLSDETREND: RATS procedure to perform local to unity GLS detrending," Statistical Software Components RTS00077, Boston College Department of Economics.
- Tom Doan, "undated". "ERSTEST: RATS procedure to perform Elliott-Rothenberg-Stock unit root tests," Statistical Software Components RTS00066, Boston College Department of Economics.
- Hui-cheng Zhou & Yong Peng & Guo-hua Liang, 2008. "The Research of Monthly Discharge Predictor-corrector Model Based on Wavelet Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(2), pages 217-227, February.
- Chan, Wai-Sum, 1999. "A comparison of some of pattern identification methods for order determination of mixed ARMA models," Statistics & Probability Letters, Elsevier, vol. 42(1), pages 69-79, March.
- Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
- Jehangir Awan & Deg-Hyo Bae, 2014. "Improving ANFIS Based Model for Long-term Dam Inflow Prediction by Incorporating Monthly Rainfall Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1185-1199, March.
- Alpaslan Yarar, 2014. "A Hybrid Wavelet and Neuro-Fuzzy Model for Forecasting the Monthly Streamflow Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 553-565, January.
- Qiang Zhang & Ben-De Wang & Bin He & Yong Peng & Ming-Lei Ren, 2011. "Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(11), pages 2683-2703, September.
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Keywords
Annual runoff forecasting; Hydrologic time series; Auto-regressive integrated moving average (ARIMA); Ensemble empirical mode decomposition (EEMD); Decomposition and ensemble;All these keywords.
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