Prediction of Daily Pan Evaporation using Wavelet Neural Networks

Water Resources Management

Volumn 26, Issue 12, 2012, Pages 3639-3652

  Abghari, Hirad ^a   Ahmadi, Hojjat ^a   Besharat, Sina ^a   Rezaverdinejad, Vahid ^a  

^a URMIA UNIVERSITY   (Iran)

Author keywords

Daily pan evaporation; Iran; Lar synoptic station; Mexican hat and PolyWOG1 mother wavelet; MLP; Wavelet neural networks

Indexed keywords

DAILY PAN EVAPORATION; IRAN; MLP; MOTHER WAVELETS; SYNOPTIC STATION; WAVELET NEURAL NETWORKS;

EVAPORATION; FORECASTING; PHASE TRANSITIONS; POWER TRANSFORMERS; TOPOLOGY; WATER SUPPLY;

THERMAL PROCESSING (FOODS);

ARTIFICIAL NEURAL NETWORK; DRINKING WATER; EVAPORATION; PREDICTION; WATER SUPPLY; WAVELET ANALYSIS;

IRAN;

EID: 84865526593     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-012-0096-z     Document Type: Article

References (43)

1. Abghari H, Nouri M, Rezaeian Zadeh M (2009) Reservoir dam inflow modeling using wavelet-base neural network and multilayer perceptron network. International Conference on Water Resources 1: 665-670, (16-18 August 2009), Shahrood, Iran.
2. Caudill M (1987) Neural networks primer, part I. AI Expert, December, 46-52.
3. Chen Y, Yang B, Dong J (2006) Time Series Prediction using a local linear wavelet neural network. Neurocomputiong 69: 449-465.
4. Dawson CW, Wilby R (1998) An artificial neural network approach to rainfall-runoff modeling. Hydrolog Sci J 43(1): 47-66.
5. Dibik YB, Solomatine DP (2001) River flow forecasting using artificial neural networks. J Phys Chem Earth 26(1): 1-7.
6. Dulkashi S, Karunasinghe K, Shie-yui L (2006) Chaotic time series prediction with global model: artificial neural network. J Hydrol 323: 92-105.
7. Gaucherel C (2002) Use of wavelet transform for temporal characterization of remote watersheds. J Hydrol 269: 101-121.
8. Govindaraju RS, Rao AR (2000) Artificial neural networks in hydrology. Kluwer Academic Publisher, Netherlands.
9. Haykin S (1994) Neural networks: a comprehensive foundation. Prentice Hall, New York.
10. Hecht-Nielsen R (1990) Neurocomputing. Addison-Wesley Publishing Company, Reading.
11. Hsu KL, Gupta HV, Sorooshian S (1995) Artificial neural network modeling of rainfall-runoff process. Water Resour Res 31(10): 2517-2530.
12. Jain A, Srinivasulu S (2006) Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques. J Hydrol 317: 291-306.
13. Jawerth B, Sweldens W (1993) An overview of wavelet based multiresolution analysis. John Wily and Sons. New York Press.
14. Kisi O (2004) River flow modeling using artificial neural networks. J Hydrolog Eng ASCE 9(1): 60-63.
15. Kisi O (2007) Streamflow forecasting using different artificial neural network algorithms. J Hydrolog Eng 12(5): 532-539.
16. Kisi O (2008) River flow forecasting and estimation using different artificial neural network techniques. J Hydrol Res 39(1): 27-40.
17. Kisi O (2009a) Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting. Hydrolog Process 23(25): 3583-3597.
18. Kisi O (2009b) Neural networks and wavelet conjunction model for intermittent streamflow forecasting. ASCE J Hydrol Eng 14(8): 773-782.
19. Lekutai G (1997) Adaptive Self-Tuning Neuro Wavelet Network Controllers, Ph. D Dissertation in the Electrical Engineering Department. Virginia Polytechnic Institute and State University.
20. Lotric U (2004) Wavelet base denoising integrated into MLP. Neurocomputing 62: 179-196.
21. Moghaddamnia A, Ghafari Gousheh M, Piri J, Amin S, Han D (2009) Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques. Adv Water Resour 32(1): 88-97.
22. Murtagh F, Starck JL, Renaud O (2004) On neuro-wavelet modeling. Decision Support Systems 37: 475-484.
23. Oussar Y, Dreyfus G (2000) Initialization by selection for wavelet network training. Neurocomputing 34: 131-143.
24. Oussar Y, Rivals I, Personnaz L, Dreyfus G (1998) Training wavelet networks for nonlinear dynamic input-output modeling. Neurocomputing 20(1-3): 173-188.
25. Partal T, Kisi O (2007) Wavelet and Neuro-fuzzy conjunction model for precipitation forecasting. J Hydrol 342: 199-212.
26. Pati YC, Krishnaparasad PS (1993) Analysis and synthesis of feedforward neural networks using discrete affine wavelet transformations. IEEE Trans Neural Networks 4(1): 73-85.
27. Rezaeian Zadeh M, Tabari H (2012) MLP-based drought forecasting in different climatic regions. Theor Appl Climatol. doi: 10. 1007/s00704-012-0592-3.
28. Rezaeian Zadeh MS, Amin D, Khalili V, Singh P (2010) Daily outflow prediction by multilayer perceptron with Logistic Sigmoid and Tangent Sigmoid activation functions. Water Resour Manage 24(11): 2673-2688. doi: 10. 1007/s11269-009-9573-4.
29. Rezaeian Zadeh M, Zand-Parsa Sh, Abghari H, Zolghadr M, Singh VP (2012a) Hourly air temperature driven using multi-layer perceptron and radial basis function networks in arid and semi-arid regions. Theor Appl Climatol. doi: 10. 1007/s00704-012-0595-0.
30. Rezaeian Zadeh M, Tabari H, Abghari H (2012b) Prediction of monthly discharge volume by different artificial neural network algorithms in semi-arid regions. Arabian Journal of Geosciences. In press. doi: 10. 1007/s12517-011-0517-y.
31. Shamseldin AY (1997) Application of neural network technique to rainfall-runoff modeling. J Hydrol 199(3-4): 272-294.
32. Sudheer KP, Gosain AK, Ramasastri KS (2002) A data driven algorithm for constructing artificial neural network rainfall-runoff models. Hydrol Process 16(6): 1325-1330.
33. Tabari H, Marofi S, Sabziparvar AA (2010) Estimation of daily pan evaporation using artificial neural network and multivariate non-linear regression. Irrigat Sci 28: 399-406.
34. Tabari H, Hosseinzadeh Talaee P, Abghari H (2012) Utility of coactive neuro-fuzzy inference system for pan evaporation modeling in comparison with multilayer perceptron. Meteorol Atmos Phys. doi: 10. 1007/s00703-012-0184-x.
35. Tao H (2006) Wavelet neural network model for forecasting exchange rate. Integrated with Genetic Algorithm. IJCSNS International Journal of Computer Science and Network Security, VOL. 6 No. 8A, 60-63. August 2006.
36. Tokar AS, Johnson A (1999) Rainfall-runoff modeling using artificial neural networks. J Hydrolog Eng ASCE 4(3): 232-239.
37. Tokar AS, Markus M (2000) Precipitation-runoff modeling using artificial neural networks and conceptual models. J Hydrolog Eng ASCE 5(2): 156-161.
38. Wajdi B, Chokri BA, Alimi M (2006) Synthesis of Wavelet Filters using Wavelet Neural Networks. Transactions on Engineering, Computing and Technology, Vol 13 MAY. 108-111. ISSN 1305-5313.
39. Wang W, Ding J (2003) Wavelet network model and its application to the prediction of hydrology. Nat Sci 1(1): 67-71.
40. Wang W, van Gelder P, Vrijling JK (2006) Forecasting daily stream flow using hybrid ANN models. J Hydrol 324: 383-399.
41. Wicher, Percival, Guttorp (1996) Wavelet Analysis of Covariance with Application to Atmospheric Time Series, NRCSE-Technical Report, No: 024.
42. Wu JS, Han J, Annambhotla S, Bryant S (2005) Artificial neural networks for forecasting watershed runoff and stream flows. J Hydrolog Eng ASCE 10(3): 216-222.
43. Zhang Q, Benveniste A (1992) Wavelet networks. IEEE Trans Neural Networks 3(6): 889-898.