A comparison of support vector machines and artificial neural networks in hydrological/meteorological time series prediction

Advances in Geosciences: Volume 6: Hydrological Science (HS)

Volumn , Issue , 2007, Pages 91-96

  Karunasingha, Dulakshi S K ^a   Liong, Shie Yui ^b  

^a UNIVERSITY OF PERADENIYA   (Sri Lanka)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84967588169     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1142/9789812708915_0009     Document Type: Chapter

References (14)

1. V. N. Vapnik, The Nature of Statistical Learning Theory, 1st Ed. (Springer, New York, 1995).
2. V. N. Vapnik, The Nature of Statistical Learning Theory, 2nd Ed. (Springer, New York, 1999).
3. D. S. K. Karunasingha and S. Y. Liong, J. Hydrol. 323 (2006) 92-105.
4. J. C. Platt, in Advances in Kernel Methods - Support Vector Learning, eds. B. Schölkopf, C. Burges and A. Smola (MIT Press, Cambridge, MA, 1999), pp. 185-208.
5. T. Joachims, in Advances in Kernel Methods - Support Vector Learning, eds. B. Schölkopf, C. Burges and A. Smola (MIT Press, Cambridge, MA, 1999), pp. 169-183.
6. J. A. K. Suykens, G. T. Van, B. J. De, M. B. De and J. Vandewalle, Least Squares Support Vector Machines (World Scientific, Singapore, 2002).
7. X. Y. Yu, S. Y. Liong and V. Babovic, J. Hydroinform. 6(3) (2004) 209-223.
8. X. Y. Yu, Support Vector Machine in Chaotic Hydrological Time Series Forecasting. PhD Thesis (National University of Singapore, Singapore, 2004).
9. R. Collobert and S. Bengio, J. Machine Learn. Res. 1 (2001) 143-160.
10. V. Cherkassky and Y. Ma, Neural Networks 17(1) (2004) 113-126.
11. C. Sivapragasam, Multi-objective Evolutionary Techniques in Defining Optimal Policies for Real-time Operation of Reservoir Systems. PhD Thesis (National University of Singapore, Singapore, 2003).
12. K. Krishnakumar, SPIE Conference on Intelligent Control and Adaptive Systems, Philadelphia, PA, Vol. 1196 (1989).
13. D. S. K. Karunasingha, Efficient and Prediction Enhancement Schemes in Chaotic Hydrological Time Series Analysis. PhD Thesis (National University of Singapore, Singapore, 2006).
14. C. Sivapragasam, S. Y. Liong and M. F. K. Pasha, J. Hydroinform. 3(2) (2001) 141-152.