Time Series Forecasting Using Wavelet-Least Squares Support Vector Machines and Wavelet Regression Models for Monthly Stream Flow Data

Show more

References

[1] H. E. Hurst, “Long Term Storage Capacity of Reservoirs,” Transactions of ASCE, Vol. 116, 1961, pp. 770-799.

[2] N. C. Matalas, “Mathematical Assessment of Symmetric Hydrology,” Water Resources Research, Vol. 3, No. 4, 1967, pp. 937-945. doi:10.1029/WR003i004p00937

[3] G. E. P. Box and G. M. Jenkins, “Time Series Analysis Forecasting and Control,” Holden Day, San Francisco, 1970.

[4] J. W. Delleur, P. C. Tao and M. L. Kavvas, “An Evaluation of the Practicality and Complexity of Some Rainfall and Runoff Time Series Model,” Water Resources Research, Vol. 12, No. 5, 1976, pp. 953-970.
doi:10.1029/WR012i005p00953

[5] V. Vapnik, “The Nature of Statistical Learning Theory,” Springer Verlag, Berlin, 1995.
doi:10.1007/978-1-4757-2440-0

[6] P. S. Yu, S. T. Chen and I. F. Chang, “Support Vector Regression for Real-Time Flood Stage Forecasting,” Journal of Hydrology, Vol. 328, No. 3-4, 2006, pp. 704-716.
doi:10.1016/j.jhydrol.2006.01.021

[7] Y. B. Dibike, S. Velickov, D. P. Solomatine and M. B. Abbott, “Model Induction with Support Vector Machines: Introduction and Applications,” Journal of Computing in Civil Engineering, Vol. 15, No. 3, 2001, pp. 208-216.
doi:10.1061/(ASCE)0887-3801(2001)15:3(208)

[8] A. Elshorbagy, G. Corzo, S. Srinivasulu and D. P. Solomatine, “Experimental Investigation of the Predictive Capabilities of Data Driven Modeling Techniques in Hydro logy, Part 1: Concepts and Methodology,” Hydrology and Earth System Sciences Discussions, Vol. 6, 2009, pp. 7055-7093.

[9] A. Elshorbagy, G. Corzo, S. Srinivasulu and D. P. Solomatine, “Experimental Investigation of the Predictive Capabilities of Data Driven Modeling Techniques in Hydro logy, Part2: Application,” Hydrology and Earth System Sciences Discussions, Vol. 6, 2009, pp. 7095-7142.

[10] T. Asefa, M. Kemblowski, M. McKee and A. Khalil, “Multi-Time Scale Stream Flow Predictions: The Support Vector Machines Approach,” Journal of Hydrology, Vol. 318, No. 1-4, 2006, pp. 7-16.

[11] J. Y. Lin, C. T. Cheng and K. W. Chau, “Using Support Vector Machines for Long-Term Discharge Prediction,” Hydrological Sciences Journal, Vol. 51, No. 4, 2006, pp. 599-612. doi:10.1623/hysj.51.4.599

[12] W. C. Wang, K. W. Chau, C. T. Cheng and L. Qiu, “A Comparison of Performance of Several Artificial Intelligence Methods for Forecasting Monthly Discharge Time Series,” Journal of Hydrology, Vol. 374, No. 3-4, 2009, pp. 294-306. doi:10.1016/j.jhydrol.2009.06.019

[13] J. A. K. Suykens and J. Vandewalle, “Least Squares Support Vector Machine Classifiers,” Neural Processing Letters, Vol. 9, No. 3, 1999, pp. 293-300.
doi:10.1023/A:1018628609742

[14] D. Hanbay, “An Expert System Based on Least Square Support Vector Machines for Diagnosis of Valvular Heart Disease,” Expert Systems with Applications, Vol. 36, No. 4, 2009, pp. 8368-8374.

[15] Y. W. Kang, J. Li, C. Y. Guang, H.-Y. Tu, J. Li and J. Yang, “Dynamic Temperature Modeling of an SOFC Using Least Square Support Vector Machines,” Journal of Power Sources, Vol. 179, No. 2, 2008, pp. 683-692.
doi:10.1016/j.jpowsour.2008.01.022

[16] B. Krishna, Y. R. Satyaji Rao and P. C. Nayak, “Time Series Modeling of River Flow Using Wavelet Neutral Networks,” Journal of Water Resources and Protection, Vol. 3, No. 1, 2011, pp. 50-59.
doi:10.4236/jwarp.2011.31006

[17] L. C. Simith, D. L. Turcotte and B. Isacks, “Streamflow Characterization and Feature Detection Using a Discrete Wavelet Transform,” Hydrological Processes, Vol. 12, No. 2, 1998, pp. 233-249.
doi:10.1002/(SICI)1099-1085(199802)12:2<233::AID-HYP573>3.0.CO;2-3

[18] D. Wang and J. Ding, “Wavelet Network Model and Its Application to the Prediction of Hydrology,” Nature and Science, Vol. 1, No. 1, 2003, pp. 67-71.

[19] D. Labat, R. Ababou and A. Mangin, “Rainfall-Runoff Relations for Karastic Springs: Part II. Continuous Wave let and Discrete Orthogonal Multiresolution Analysis,” Journal of Hydrology, Vol. 238, No. 3-4, pp. 2000, pp. 149-178. doi:10.1016/S0022-1694(00)00322-X

[20] S. G. Mallat, “A Theory for Multi Resolution Signal De composition: The Wavelet Representation,” IEEE Trans actions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 7, 1998, pp. 674-693.

[21] A. Grossman and J. Morlet, “Decomposition of Harley Functions into Square Integral Wavelets of Constant Shape,” SIAM Journal on Mathematical Analysis, Vol. 15, No. 4, 1984, pp. 723-736. doi:10.1137/0515056

[22] I. Daubechies, “Orthogonal Bases of Compactly Supported Wavelets,” Communications on Pure and Applied Mathematics, Vol. 41, No. 7, 1988, pp. 909-996.
doi:10.1002/cpa.3160410705

[23] E. Foufoula-Georgiou and P. E Kumar, “Wavelets in Geophysics,” Academic, San Diego and London, 1994.

[24] R. M. Rao and A. S. Bopardikar, “Wavelet Transforms: Introduction to Theory and Applications,” Addison Wesley Longman, Inc., Reading, 1998, 310 p.

[25] M. Kucuk and N. Agiralio?lu, “Wavelet Regression Technique for Streamflow Prediction,” Journal of Applied Statistics, Vol. 33, No. 9, 2006, pp. 943-960.
doi:10.1080/02664760600744298

[26] O. Kisi, “Wavelet Regression Model as an Alternative to Neural Networks for Monthly Streamflow Forecasting,” Hydrological Processes, Vol. 23, No. 25, 2009, pp. 3583-3597. doi:10.1002/hyp.7461

[27] O. Kisi, “Wavelet Regression Model for Short-Term Streamflow Forecasting,” Journal of Hydrology, Vol. 389, No. 3-4, 2010, pp. 344-353.
doi:10.1016/j.jhydrol.2010.06.013

[28] P. Y. Ma, “A Fresh Engineering Approach for the Fore cast of Financial Index Volatility and Hedging Strategies,” PhD thesis, Quebec University, Montreal, 2006.

[29] M. Firat, “Comparison of Artificial Intelligence Techniques for River Flow Forecasting,” Hydrology and Earth System Sciences, Vol. 12, No. 1, 2008, pp. 123-139.

[30] R. Samsudin, S. Ismail and A. Shabri, “A Hybrid Model of Self-Organizing Maps (SOM) and Least Square Support Vector Machine (LSSVM) for Time-Series Fore casting,” Expert Systems with Applications, Vol. 38, No. 8, 2011, pp. 10574-10578.

[31] M. T. Gencoglu and M. Uyar, “Prediction of Flashover Voltage of Insulators Using Least Square Support Vector Machines,” Expert Systems with Applications, Vol. 36, No. 7, 2009, pp. 10789-10798.
doi:10.1016/j.eswa.2009.02.021

[32] L. Liu and W. Wang, “Exchange Rates Forecasting with Least Squares Support Vector Machines,” International Conference on Computer Science and Software Engineering, Wuhan, 12-14 December 2008, pp. 1017-1019.