Least squares support vector machine for short-term prediction of meteorological time series

Theoretical and Applied Climatology

Volumn 111, Issue 1-2, 2013, Pages 297-307

  Mellit, A ^a,d   Pavan, A Massi ^b   Benghanem, M ^c  

^a UNIVERSITY OF JIJEL   (Algeria)

^b UNIVERSITY OF TRIESTE   (Italy)

^c TAIBAH UNIVERSITY   (Saudi Arabia)

^d ABDUS SALAM INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; LEAST SQUARES METHOD; MODEL TEST; MODEL VALIDATION; PREDICTION; TIME SERIES ANALYSIS; VECTOR; WEATHER FORECASTING;

EID: 84871934974     PISSN: 0177798X     EISSN: 14344483     Source Type: Journal    
DOI: 10.1007/s00704-012-0661-7     Document Type: Article

References (43)

1. Aguiar RJ, Collares-Perrira M, Conde JP (1988) Simple procedure for generating sequences of daily radiation values using library of Markov transition matrices. Sol Energy 40: 269-279.
2. Barbounis TG, Theocharis JB (2007) Locally recurrent neural networks for wind speed prediction using spatial correlation. Inform Sci 177: 5775-5797.
3. Cao LJ, Tay EH (2001) Support vector with adaptive parameters in financial time series forecasting. IEEE Trans Neural Netw 14: 1506-1518.
4. Danilo PM, Jonathon AC (2001) Recurrent neural networks for prediction. Wiley, New York.
5. Deng S, Yeh TH (2010) Applying least squares support vector machines to the airframe wing-box structural design cost estimation. Expert Syst Appl. doi: 10. 1016/j. eswa. 2010. 05. 038.
6. Elsner JB, Tsonis AA (1992) Nonlinear prediction, chaos and noise. Bull Am Meteorol Soc 73: 49-60.
7. Flake GW, Lawrence S (2002) Efficient SVM regression training with SMO. Mach Learn 46: 271-290.
8. Flecher R (1987) Practical methods of optimization. Wiley, New York.
9. Frank J, Massey JR (1951) The Kolmogorov-Smirnov test for goodness of fit. J Am Stat Assoc 46: 68-78.
10. Gentle JE (2002) Elements of computational statistics. Springer, New York.
11. Gomez V, Casanovas A (2003) Fuzzy modelling of solar irradiance on inclined surfaces. Sol Energy 75: 307-315.
12. Hsu CW, Lin CJ (2002) A comparison of methods for multiclass support vector machines. IEEE Trans Neural Netw 13: 415-425.
13. Kretzschmar R, Eckert P, Cattani D (2004) Neural network classifiers for local wind prediction. MeteoSwiss, Geneva, Switzerland 43: 727-738.
14. Kuligowaki RJ, Barros AP (1998) Experiments in short-term precipitation forecasting using artificial neural networks. Mon Weather Rev 126: 470-482.
15. Macchiato MF, Rotonda L, Lapenna V, Ragosta M (1995) Time modelling and spatial clustering of daily ambient temperature: an application in southern Italy. Environmetrics 6: 31-53.
16. Maqsood I, Abraham A (2007) Weather analysis using ensemble of connectionist learning paradigms. Appl Soft Comput 7: 995-1004.
17. Maqsood I, Khan M (2004) An ensemble of neural networks for weather forecasting. Neural Comput Appl 13: 112-122.
18. Matyasovszky I (2001) A nonlinear approach to modelling climatological time series. Theor Appl Climatol 69: 139-147.
19. Mellit A (2009) Artificial intelligence techniques for modeling and forecasting of meteorological data: a survey. In: Lang RP, Lombargo SF (eds) Atmospheric turbulence, meteorological modeling and aerodynamics. Nova, USA.
20. Mellit A, Benghanem M, Hadj AA, Guessoum A (2005) A simplified model for generating sequences of global radiation data for isolated sites: using artificial neural network and a library of Markov transition matrices. Sol Energy 79(5): 468-482.
21. Mellit A, Benghanem M, Kalogirou SA (2006) An adaptive wavelet-network model for forecasting daily total solar radiation. Appl Energy 83(7): 705-722.
22. Mellit A, Kalogirou SA, Shaari S, Salhi H, Hadj Arab A (2008) Methodology for predicting sequences of mean monthly clearness index and daily solar radiation data in remote areas: application for sizing a stand-alone PV system. Renew Energy 33(7): 1570-1590.
23. Mellit A, Eleuch H, Benghanem M, Elaoun C, Pavan AM (2010) An adaptive model for predicting of global, direct and diffuse hourly solar irradiance. Energy Convers Manag 51: 771-782.
24. Mellit A, Mekki H, Adnane M, Kalogirou SA (2011) FPGA-based implementation of intelligent predictor for global solar irradiation. Part I: theory and simulation. Expert Syst Appl 38: 2668-2685.
25. Miller A (2002) Subset selection in regression. Chapman & Hall/CRC, New York.
26. Moghaddamnia A, Remesan R, Hassanpour KM, Mohammadi M, Han Piri DJ (2009) Comparison of LLR, MLP, Elman, NNARX and ANFIS models-with a case study in solar radiation estimation. J Atmos Sol-Terr Phys 71(8-9): 975-982.
27. Palit AK, Popovic D (2005) Computational intelligence in time series forecasting: theory and engineering applications. Springer, New York.
28. Perez-Munuzuri V, Gelpi IR (2000) Application of nonlinear forecasting techniques for meteorological modelling. Ann Geophys 18: 1349-1359.
29. Radhika Y, Shashi M (2009) Atmospheric temperature prediction using support vector machines. Int J Comput Theory Eng 1: 1793-8201.
30. Samsudin R, Shabri A, Saad P (2010) A comparison of time series forecasting using support vector machine and artificial neural network model. J Appl Sci 10: 950-958.
31. Samuia P, Kothari DP (2011) Utilization of a least square support vector machine (LSSVM) for slope stability analysis. Sci Iran A 18(1): 53-58.
32. Schölkopf B, Smola AJ (2002) Learning with kernels. MIT, Cambridge.
33. Sharon D (1967) On the further development of Gringorten's stochastic model for climatological predictions. J Appl Meteorol 6: 625-630.
34. Shuichi H, Mamoru M, Toshikazu I (1991) Statistical time series models of solar radiation and outdoor temperature identification of seasonal models by Kalman filter. Energy Build 15(3-4): 373-383.
35. Silverman D, Dracup JA (2000) Artificial neural networks and long-range precipitation prediction in California. J Appl Meteorol 39: 57-66.
36. Snell SE, Gopal S, Kaufmann RK (2000) Spatial interpolation of surface air temperatures using artificial neural networks: evaluating their use for downscaling GCMs. J Clim 13: 886-895.
37. Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9: 293-300.
38. Tasadduq I, Rehman S, Bubshait K (2002) Application of neural networks for the prediction of hourly mean surface temperatures in Saudi Arabia. Renew Energy 25: 545-554.
39. Tulcan-paulescu E, Paulescu M (2007) Fuzzy modelling of solar irradiation using air temperature data. Theor Appl Climatol 91(1-4): 181-192.
40. Vapnik V (1999) The nature of statistical learning theory, 2nd edn. Springer, New York.
41. Wanga W, Mena C, Lub W (2008) Online prediction model based on support vector machine. Neurocomputing 71: 550-558.
42. Yuval Y (2000) Neural network training for prediction of climatological time series, regularized by minimization of the generalized cross-validation function. Am Meteorol Soc 128: 456-1473.
43. Zeng Z, Wang J (2010) Advances in neural network research and applications, lecture notes in electrical engineering, vol 67. Springer, New York.