Comparative study of monthly inflow prediction methods for the Three Gorges Reservoir

Stochastic Environmental Research and Risk Assessment

Volumn 28, Issue 3, 2014, Pages 555-570

  Wang, Yun ^a   Guo, Shenglian ^a   Chen, Hua ^a   Zhou, Yanlai ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Genetic programming; Monthly inflow prediction; Seasonal autoregressive; Singular spectrum analysis; Support vector machine; Three Gorges Reservoir

Indexed keywords

EFFICIENCY; FORECASTING; GENETIC ALGORITHMS; GENETIC PROGRAMMING; INFORMATION FILTERING; RESERVOIRS (WATER); SPECTRUM ANALYSIS; SUPPORT VECTOR MACHINES;

AUTO-REGRESSIVE; INFLOW PREDICTIONS; PRE-PROCESSING METHOD; PREDICTION PRECISION; QUASI-PERIODIC SIGNALS; SCIENTIFIC KNOWLEDGE; SINGULAR SPECTRUM ANALYSIS; THREE GORGES RESERVOIR;

PREDICTIVE ANALYTICS;

EID: 84892843737     PISSN: 14363240     EISSN: 14363259     Source Type: Journal    
DOI: 10.1007/s00477-013-0772-4     Document Type: Article

References (42)

1. Aksoy H, Dahamsheh A (2009) Artificial neural network models for forecasting monthly precipitation in Jordan. Stoch Environ Res Risk Assess 23(7): 917-931.
2. Aytek A, Alp M (2008) An application of artificial intelligence for rainfall runoff modeling. J Earth Syst Sci 117(2): 145-155.
3. Bray M, Han D (2004) Identification of support vector machines for runoff modeling. J Hydroinform 6: 265-280.
4. Cao LJ, Tay FEH (2003) Support vector machine with adaptive parameters in financial time series forecasting. IEEE Trans Neural Netw 14(6): 1506-1518.
5. Chang FJ, Chen YC (2001) A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction. J Hydrol 245: 153-164.
6. Chau KW, Wu CL (2010) A hybrid model coupled with singular spectrum analysis for daily rainfall prediction. J Hydroinform 12(4): 458-473.
7. Chen PW, Wang, JY, Lee HM (2004) Model selection of SVMs using GA approach. In: IEEE international joint conference on neural networks (3), pp 2035-2040.
8. Dong B, Cao C, Lee SE (2005) Applying support vector machines to predict building energy consumption in tropical region. Energy Build 37: 545-553.
9. Golyandina N, Nekrutkin V, Zhigljavsky A (2001) Analysis of time series structure: SSA and the related techniques. Chapman & Hall/CRC, Boca Raton.
10. Hsu KL, Gupta HV, Sorooshian S (1995) Artificial neural network modeling of the rainfall-runoff process. Water Resour Res 31(10): 2517-2530.
11. Hsu CW, Chang CC, Lin CJ (2003) A practical guide to support vector classification. http://www. csie. ntu. edu. tw/~cjlin/papers/guide/guide. pdf.
12. Kisi O, Shiri J (2011) Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models. Water Resour Manag 25(13): 3135-3152.
13. Kisi O, Dailr AH, Cimen M, Shiri J (2012) Suspended sediment modeling using genetic programming and soft computing techniques. J Hydrol 450-451: 48-58.
14. Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection. The MIT Press, Cambridge.
15. Lin JY, Cheng CT, Chau KW (2006) Using support vector machines for long-term discharge prediction. Hydrol Sci J 51(4): 599-612.
16. Lin GF, Chen GR, Wu MC, Chou YC (2009) Effective forecasting of hourly typhoon rainfall using support vector machines. Water Resour Res 45: W08440. doi: 10. 1029/2009WR007911.
17. Liong SY, Sivapragasm C (2002) Hood stage forecasting with SVM. J Am Water Resour Assoc 38(1): 173-186.
18. Liong SY, Gautam TR, Khu ST, Babovic V, Keijzer M, Muttil N (2002) Genetic programming: a new paradigm in rainfall runoff modeling. J Am Water Resour Assoc 38(3): 705-718.
19. Makkeasorn A, Chang NB, Zhou X (2008) Short-term streamflow forecasting with global climate change implications-a comparative study between genetic programming and neural network models. J Hydrol 352: 336-354.
20. Marques CAF, Ferreira J, Rocha A, Castanheira J, Goncalves P, Vaz N, Dias JM (2006) Singular spectral analysis and forecasting of hydrological time series. Phys Chem Earth 31: 1172-1179.
21. Matalas NC (1967) Mathematical assessment of synthetic hydrology. Water Resour Res 3(4): 937-945.
22. MWR (Ministry of Water Resources) (2000) Standard for hydrological information and hydrological forecasting (SL250-2000) (in Chinese).
23. Nayak PC, Sudheer KP, Ramasastri KS (2005) Fuzzy computing based rainfall-runoff model for real time flood forecasting. Hydrol Process 19(4): 955-968.
24. Noori R, Karbassi AR, Moghaddamnia A, Han D, Zokaei-Ashtiani MH, Farokhnia A, Gousheh MG (2011) Assessment of input variables determination on the SVM model performance using PCA, Gamma test, and forward selection techniques for monthly stream flow prediction. J Hydrol 401: 177-189.
25. Salas JD, Boes DC, Smith RA (1982) Estimation of ARMA models with seasonal parameters. Water Resour Res 18(4): 1006-1010.
26. Sheta A, Mahmoud A (2001) Forecasting river flow using genetic programming. In: Proceedings of the 33rd southeastern symposium on system theory, March 2001, Cairo, pp 343-347.
27. Sivakumar B (2009) Nonlinear dynamics and chaos in hydrologic systems: latest developments and a look forward. Stoch Environ Res Risk Assess 23(7): 1027-1036.
28. Sivapragasam C, Liong SY, Pasha MFK (2001) Rainfall and runoff forecasting with SSA-SVM approach. J Hydroinform 3(7): 141-152.
29. Vapnik V (1995) The nature of statistical learning theory. Springer, New York.
30. Vautard R, Yiou P, Ghil M (1992) Singular-spectrum analysis: a toolkit for short, noisy and chaotic signals. Physica D 58: 95-126.
31. Wang WJ, Xu ZB, Lu WZ, Zhang XY (2003) Determination of the spread parameter in the Gaussian kernel for classification and regression. Neurocomputing 55: 643-663.
32. Wang WC, Chau KW, Cheng CT, Qiu L (2009a) A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series. J Hydrol 374: 294-306.
33. Wang WS, Jin JL, Li YQ (2009b) Prediction of inflow at Three Gorges Dam in Yangtze River with wavelet network model. Water Resour Manag 23: 2791-2803.
34. Wang WC, Cheng CT, Chau KW, Xu DM (2012) Calibration of Xinanjiang model parameters using hybrid genetic algorithm based fuzzy optimal model. J Hydroinform 14(3): 784-799.
35. Whigam PA, Crapper PF (2001) Modelling rainfall-runoff relationships using genetic programming. Math Comput Model 33: 707-721.
36. Wu CL, Chau KW (2011) Rainfall-runoff modeling using artificial neural network coupled with singular spectrum analysis. J Hydrol 399: 394-409.
37. Wu CL, Chau KW, Li YS (2009) Predicting monthly streamflow using data-driven models coupled with data-preprocessing techniques. Water Resour Res 45: W08432. doi: 10. 1029/2007WR006737.
38. Xiong LH, Guo SL (2004) Trend test and change-point detection for the annual discharge series of the Yangtze River at the Yichang hydrological station. Hydrol Sci J 49(1): 99-112.
39. Xu KQ, Brown C, Kwon HH, Lall U, Zhang JQ, Hayashia S, Chene ZY (2007) Climate teleconnections to Yangtze River seasonal streamflow at the Three Gorges Dam. China Int J Climatol 27: 771-780.
40. Yoon H, Jun SC, Hyun Y, Bae GO, Lee KK (2011) A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. J Hydrol 396: 128-138.
41. Yu PS, Chen ST, Chang IF (2006) Support vector regression for real-time flood stage forecasting. J Hydrol 328: 704-716.
42. Zhang Q, Wang BD, He B, Peng Y, Ren ML (2011) Singular spectrum analysis and ARIMA hybrid model for annual runoff forecasting. Water Resour Manag 25: 2683-2703.