Predicting rainfall in the context of rainfall derivatives using genetic programming

Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015

Volumn , Issue , 2015, Pages 711-718

  Cramer, Sam ^a   Kampouridis, Michael ^a   Freitas, Alex A ^a   Alexandridis, Antonis ^a  

^a UNIVERSITY OF KENT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORECASTING; GENETIC ALGORITHMS; GENETIC PROGRAMMING; MARKOV PROCESSES; WATER RESOURCES;

CHAIN-EXTENDED; PROBLEM DOMAIN; RAINFALL PREDICTION; TIME-SERIES DATA; WATER RESOURCE PLANNING;

RAIN;

EID: 84964977693     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SSCI.2015.108     Document Type: Conference Paper

References (13)

1. D. S. Wilks, "Multisite generalization of a daily stochastic precipitation generation model," Journal of Hydrology, vol. 210, pp. 178-191, Sep. 1998.
2. B. L. Cabrera, M. Odening, and M. Ritter, "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers, Jan. 2013.
3. M. Ritter, O. Muhoff, and M. Odening, "Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model," Computational Economics, vol. 44, no. 1, pp. 67-86, 2014.
4. G. Leobacher and P. Ngare, "On modelling and pricing rainfall derivatives with seasonality," Applied Mathematical Finance, vol. 18, no. 1, pp. 71-91, 2011.
5. R. W. Katz, "Precipitation as a chain-dependent process," Journal of Applied Meteorology and Climatology, vol. 16, no. 7, pp. 671-676, 1977.
6. N. Q. Hung, M. S. Babel, S. Weesakul, and N. K. Tripathi, "An artificial neural network model for rainfall forecasting in bangkok, thailand," Hydrology and Earth System Sciences, vol. 13, no. 8, pp. 1413-1425, 2009.
7. H. Weerasinghe, H. Premaratne, and D. Sonnadara, "Performance of neural networks in forecasting daily precipitation using multiple sources," Journal of the National Science Foundation of Sri Lanka, vol. 38, no. 3, 2010.
8. O. Kisi and J. Shiri, "Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models," Water Resources Management, vol. 25, no. 13, pp. 3135-3152, 2011.
9. D. A. Woolhiser and G. G. S. Pegram, "Maximum Likelihood Estimation of Fourier Coefficients to Describe Seasonal Variations of Parameters in Stochastic Daily Precipitation Models." Journal of Applied Meteorology, vol. 18, pp. 34-42, Jan. 1979.
10. J. Koza, Genetic Programming: On the programming of computers by means of natural selection. MIT Press, 1992.
11. D. J. Montana, "Strongly typed genetic programming," Evolutionary Computation, vol. 3, no. 2, pp. 199-230, 1995.
12. M. Ĺopez-Ibáñez, J. Dubois-Lacoste, T. Stützle, and M. Birattari, "The Rpackageirace package, iterated race for automatic algorithm configuration," IRIDIA, Université Libre de Bruxelles, Belgium, Tech. Rep., 2011.
13. F. Wilcoxon, "Individual comparisons by ranking methods," Biometrics Bulletin, vol. 1, no. 6, pp. pp. 80-83, 1945.