Neural network and wavelet conjunction model for modelling monthly level fluctuations in Turkey

Hydrological Processes

Volumn 23, Issue 14, 2009, Pages 2081-2092

  Kişi, Özür ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

Discrete wavelet transform; Forecast; Lake level; Neural networks

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COMPARISON RESULT; DETERMINATION COEFFICIENTS; FORECAST; LAKE LEVEL; LAKE LEVELS; LEVEL FLUCTUATION; LONG-TERM FORECAST; RELATIVE ERRORS; ROOT MEAN SQUARE ERRORS;

BLOCK CODES; DISCRETE WAVELET TRANSFORMS; ERRORS; FORECASTING; MEAN SQUARE ERROR; NEURAL NETWORKS;

LAKES;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; ERROR ANALYSIS; FORECASTING METHOD; HYDROLOGICAL MODELING; LAKE LEVEL; NUMERICAL MODEL; TRANSFORM; WAVELET ANALYSIS;

EGIRDIR LAKE; EURASIA; ISPARTA [TURKEY]; LAKE VAN; TURKEY;

EID: 67650333111     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.7340     Document Type: Article

References (36)

1. Altunkaynak A. 2007. Forecasting surface water level fluctuations of Lake Van by artificial neural networks. Water Resources Management 21: 399-408.
2. Anctil F, Tape DG. 2004. An exploration of artificial neural network rainfall-runoff forecasting combined with wavelet decomposition. Journal of Environmental Engineering and Science 3: 121-128.
3. Bae D-H, Jeong DM, Kim G. 2007. Monthly dam inflow forecasts using weather forecasting information and neuro-fuzzy technique. Hydrological Sciences Journal 52(1): 99-113.
4. Cigizoglu HK. 2003. Estimation, forecasting and extrapolation of flow data by artificial neural networks. Hydrological Sciences Journal 48(3): 349-361.
5. Cigizoglu HK, Kisi O. 2005. Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data. Nordic Hydrology 36(1): 49-64.
6. Cigizoglu HK, Kisi O. 2006. Methods to improve the neural network performance in suspended sediment estimation. Journal of Hydrology 317: 221-238.
7. Coulibaly P, Burn HD. 2004. Wavelet analysis of variability in annual Canadian streamflows. Water Resources Research 40: W03105.
8. Dawson WC, Wilby R. 1998. An artificial neural network approach to rainfall-runoff modeling. Hydrological Sciences Journal 43(1): 47-66.
9. Giustolisi O, Laucelli D. 2005. Improving generalization of artificial neural networks in rainfall-runoff modeling. Hydrological Sciences Journal 50(3): 439-457.
10. Hagan MT, Menhaj MB. 1994. Training feed forward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks 6: 861-867.
11. Haykin S. 1998. Neural Networks - A Comprehensive Foundation, 2nd edn. Prentice-Hall: Upper Saddle River, NJ; 26-32.
12. Hu TS, Lam KC, Thomas NGS. 2005. A modified neural network for improving river flow prediction. Hydrological Sciences Journal 50(2): 299-318.
13. Jain SK, Das D, Srivastava DK. 1999. Application of ANN for reservoir inflow prediction and operation. Journal of Water Resources Planning Management ASCE 125(5): 263-271.
14. Jayawardena AW, Xu PC, Tsang FL, Li WK. 2006. Determining the structure of a radial basis function network for prediction of nonlinear hydrological time series. Hydrological Sciences Journal 51(1): 21-44.
15. Karunanithi N, Grenney WJ, Whitley D, Bovee K. 1994. Neural networks for river flow prediction. Journal of Computing in Civil Engineering ASCE 8(2): 201-220.
16. Kim TW, Valdes JB. 2003. Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. Journal of Hydrologic Engineering ASCE 6: 319-328.
17. Kisi O. 2004a. River flow modeling using artificial neural networks. Journal of Hydrologic Engineering ASCE 9(1): 60-63.
18. Kisi O. 2004b. Multi-layer perceptrons with Levenberg-Marquardt optimization algorithm for suspended sediment concentration prediction and estimation. Hydrological Sciences Journal 49(6): 1025-1040.
19. Kisi O. 2005a. Daily river flow forecasting using artificial neural networks and auto-regressive models. Turkish Journal of Engineering and Environmental Sciences 29: 9-20.
20. Kisi O. 2005b. Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrological Sciences Journal 50(4): 683-696.
21. Kisi O. 2007. Stream flow forecasting using different artificial neural network algorithms. Journal of Hydrological Engineering ASCE 12(5): 532-539.
22. Kisi O. 2008a. Stream flow forecasting using neuro-wavelet technique. Hydrological Processes 22(20): 4142-4152.
23. Kisi O. 2008b. River flow forecasting and estimation using different artificial neural network techniques. Hydrology Research 39(1): 27-40.
24. Lu RY. 2002. Decomposition of interdecadal and interannual components for North China rainfall in rainy season. Chinese Journal of Atmosphere (in Chinese) 26: 611-624.
25. Mallat SG. 1989. A theory for multi resolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(7): 674-693.
26. Marquardt D. 1963. An algorithm for least squares estimation of nonlinear parameters. Journal of the Society for Industrial and Applied Mathematics 11: 431-441.
27. Ning M, Yunping C. 1998. An ANN and wavelet transformation based method for short term load forecast. Energy management and power delivery, Proceedings of Energy Management and Power Delivery, vol. 2. 405-410.
28. Ondimu S, Murase H. 2007. Reservoir level forecasting using neural networks: Lake Naivasha. Biosystems Engineering 96(1): 135-138.
29. Partal T, Küçük M. 2006. Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region (Turkey). Physics and Chemistry of the Earth 31: 1189-1200.
30. Sen Z, Kadioglu M, Batur E. 2000. Stochastic modelling of the Van Lake monthly level fluctuations in Turkey. Theoretical and Applied Climatology 65: 99-110.
31. Smith LC, Turcotte DL, Isacks B. 1998. Stream flow characterization and feature detection using a discrete wavelet transform. Hydrological Processes 12: 233-249.
32. Solomatine DP, Dulal KN. 2003. Model trees as an alternative to neural networks in rainfall-runoff modeling. Hydrological Sciences Journal 48(3): 399-411.
33. Sudheer KP, Gosain AK, Rangan DM, Saheb SM. 2002. Modelling evaporation using an artificial neural network algorithm. Hydrological Processes 16: 3189-3202.
34. Tayfur G. 2002. Artificial neural networks for sheet sediment transport. Hydrological Sciences Journal 47(6): 879-892.
35. Wang W, Ding J. 2003. Wavelet network model and its application to the prediction of the hydrology. Nature and Science 1(1): 67-71.
36. Xingang D, Ping W, Jifan C. 2003. Multiscale characteristics of the rainy season rainfall and interdecadal decaying of summer monsoon in North China. Chinese Science Bulletin 48: 2730-2734.