A Hybrid Wavelet and Neuro-Fuzzy Model for Forecasting the Monthly Streamflow Data

Water Resources Management

Volumn 28, Issue 2, 2014, Pages 553-565

  Yarar, Alpaslan ^a  

^a SELCUK UNIVERSITY   (Turkey)

Author keywords

Anfis; ARIMA; Streamflow modeling; Wavelet

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS; ARIMA; AUTO REGRESSIVE INTEGRATED MOVING AVERAGE MODELS; COMPUTER AIDED METHODS; ROOT MEAN SQUARED ERRORS; STREAMFLOW MODELING; WAVELET;

FORECASTING; MODELS;

STREAM FLOW;

ACCURACY ASSESSMENT; FORECASTING METHOD; FUZZY MATHEMATICS; NUMERICAL MODEL; STREAMFLOW;

SAKARYA BASIN; TURKEY;

EID: 84892482238     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-013-0502-1     Document Type: Article

References (28)

1. Adamowski J, Sun K (2010) Development of a coupled wavelet transform and network method for flow forecasting of non-perennial rivers in semi-arid watersheds. J Hydrol 390: 85-91.
2. Baratti R, Cannas B, Fanni A, Pintus M, Sechi GM, Toreno N (2003) River flow forecast for reservoir management through neural networks. Neurocomputing 55(3-4): 421-437.
3. Chang FJ, Chen YC (2001) A counterpropagation fuzzy-neural network modeling approach to real time stream flow prediction. J Hydrol 245: 153-164.
4. Chang LC, Chang FJ, Chiang YM (2004) A two-step-ahead recurrent neural network for stream-flow forecasting. Hydrol Process 18(1): 81-92.
5. Chen SH, Lin YH, Chang LC, Chang FJ (2006) The strategy of building a flood forecast model by neuro-fuzzy network. Hydrol Process 20: 1525-1540.
6. Dawson CW, Wilby RL (1998) An artificial neural network approach to rainfall-runoff modeling. Hydrol Sci 43(1): 47-67.
7. Dorum A, Yarar A, Sevimli MF, Onüçyildiz M (2010) Modelling the rainfall-runoff data of susurluk basin. Expert Syst Appl 37: 6587-6593.
8. Drake JT (2000) Communications phase synchronization using the adaptive network fuzzy inference system. Ph. D. Thesis, New Mexico State University, Las Cruces, New Mexico, USA.
9. El-Shafie A, Taha MR, Noureldin A (2007) A neuro-fuzzy model for inflow forecasting of the Nile River at Aswan High Dam. Water Resour Manag 21(3): 533-556.
10. Grimes DIF, Coppola E, Verdecchia M, Visconti G (2003) A neural network approach to real-time rainfall estimation for Africa using satellite data. J Hydrometeorol 4: 1119-1133.
11. Hasebe M, Nagayama Y (2002) Reservoir operation using the neural network and fuzzy systems for dam control and operation support. Adv Eng Softw 33(5): 245-260.
12. Haykin S (1998) Neural networks-a comprehensive foundation, 2nd edn. Prentice-Hall, Upper Saddle River, pp 26-32.
13. Jang J-SR (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cyberm 23(3): 665-685.
14. Jang J-SR, Sun C-T, Mizutani E (1997) Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, Upper Saddle River.
15. Kisi O (2009) Neural networks and wavelet conjunction model for intermittent streamflow forecasting. J Hydrol Eng ASCE 14(8): 773-782.
16. Kisi O (2010) Wavelet regression model for short-term streamflow forecasting. J Hydrol 389: 344-353.
17. Kisi O, Shiri J (2011) Precipitation forecasting using wavelet genetic programming and wavelet-neuro-fuzzy conjunction models. Water Resour Manag 25(13): 3135-3152.
18. Kisi O, Karahan ME, Şen Z (2006) River suspended sediment modelling using a fuzzy logic approach. Hydrol Process 20: 4351-4362.
19. Lane SN (2007) Assessment of rainfall-runoff models based upon wavelet analysis. Hydrol Process 21: 586-607.
20. Luk KC, Ball JE, Sharma A (2000) A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting. J Hydrol 227: 56-65.
21. Mallat S (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7): 674-693.
22. Sang YF (2012) A practical guide to discrete wavelet decomposition of hydrological time series. Water Resour Manag 26(11): 3345-3365.
23. Sanikhani H, Kisi O (2012) River flow estimation and forecasting by using two different adaptive neuro-fuzzy approaches. Water Resour Manag 26(6): 1715-1729.
24. Shiri J, Kisi O (2010) Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model. J Hydrol 394: 486-493.
25. Smith LC, Turcotte DL, Isacks B (1998) Stream flow characterization and feature detection using a discrete wavelet transform. Hydrol Process 12: 233-249.
26. Toprak ZF, Cigizoglu HK (2008) Predicting longitudinal dispersion coefficient in natural streams by artificial intelligence methods. Hydrol Process 22: 4106-4129.
27. Wei S, Song J, Khan NI (2012) Simulating and predicting river discharge time series using a wavelet-neural network hybrid modelling approach. Hydrol Process 26: 281-296.
28. Yarar A, Onucyi{dotless}ldi{dotless}z M, Copty NK (2009) Modelling level changes in lakes using neuro-fuzzy and artificial neural networks. J Hydrol 365: 329-334.