- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 376010, 13 pages
New Optimal Weight Combination Model for Forecasting Precipitation
1School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China
2The Key Laboratory of Water and Sediment Sciences, State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Received 9 February 2012; Accepted 21 March 2012
Academic Editor: Ming Li
Copyright © 2012 Song-shan Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- X. H. Yang, D. X. She, Z. F. Yang, Q. H. Tang, and J. Q. Li, “Chaotic bayesian method based on multiple criteria decision making (MCDM) for forecasting nonlinear hydrological time series,” International Journal of Nonlinear Sciences and Numerical Simulation, vol. 10, no. 11-12, pp. 1595–1610, 2009.
- M. Li, C. Cattani, and S. Y. Chen, “Viewing sea level by a one-dimensional random function with long memory,” Mathematical Problems in Engineering, vol. 2011, Article ID 654284, 13 pages, 2011.
- K. W. Chau, “Particle swarm optimization training algorithm for ANNs in stage prediction of Shing Mun River,” Journal of Hydrology, vol. 329, no. 3-4, pp. 363–367, 2006.
- X. H. Yang, X. J. Zhang, X. X. Hu, Z. F. Yang, and J. Q. Li, “Nonlinear optimization set pair analysis model (NOSPAM) for assessing water resource renewability,” Nonlinear Processes in Geophysics, vol. 18, no. 5, pp. 599–607, 2011.
- K. W. Chau, C. L. Wu, and Y. S. Li, “Comparison of several flood forecasting models in Yangtze River,” Journal of Hydrologic Engineering, vol. 10, no. 6, pp. 485–491, 2005.
- J. X. Xu, Y. D. Liu, Z. Z. Zhang, and Y. B. Li, “Ordinal-set pair prediction model and application in Liao river basin,” in Computer Informatics Cybernetics and Applications, vol. 1 of Lecture Notes in Electrical Engineering 107, chapter 42, pp. 395–402, 2012.
- D. Broomhead and D. Lowe, “Multivariable functional interpolation and adaptive networks,” Complex Systems, vol. 2, pp. 321–355, 1988.
- M. Alp and H. K. Cigizoglu, “Suspended sediment load simulation by two artificial neural network methods using hydro meteorological data,” Environmental Modelling & Software, vol. 22, no. 1, pp. 2–13, 2007.
- Q. Duan, N. K. Ajami, X. Gao, and S. Sorooshian, “Multi-model ensemble hydrologic prediction using Bayesian model averaging,” Advances in Water Resources, vol. 30, no. 5, pp. 1371–1386, 2007.
- J. M. Bates and C. W. J. Granger, “The combination of forecasts,” Operational Research Quarterly, vol. 20, no. 4, pp. 451–468, 1969.
- J. P. Dickinson, “Some statistical results in the combination of forecasts,” Operational Research Quarterly, vol. 24, no. 2, pp. 253–260, 1973.
- J. P. Dickinson, “Some comments on the combination of forecasts,” Operational Research Quarterly, vol. 26, no. 1, pp. 205–210, 1975.
- P. Newbold and C. W. J. Granger, “Experience with forecasting univariate time series and the combination of forecasts,” Journal of the Royal Statistical Society A, vol. 137, no. 2, pp. 131–146, 1974.
- M. Li and W. Zhao, “Visiting power laws in cyber-physical networking systems,” Mathematical Problems in Engineering, vol. 2012, Article ID 302786, 13 pages, 2012.
- A. Y. Shamseldin and K. M. O'Connor, “A real-time combination method for the outputs of different rainfall-runoff models,” Hydrological Sciences Journal, vol. 44, no. 6, pp. 895–912, 1999.
- A. E. Raftery, F. Balabdaoui, T. Gneiting, and M. Polakowski, “Using Bayesian model averaging to calibrate forecast ensembles,” Monthly Weather Review, vol. 133, no. 5, pp. 1155–1174, 2005.
- C. T. Cheng, C. P. Ou, and K. W. Chau, “Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration,” Journal of Hydrology, vol. 268, no. 1–4, pp. 72–86, 2002.
- N. K. Ajami, Q. Duan, X. Gao, and S. Sorooshian, “Multi-model combination techniques for hydrological forecasting: application to distributed model intercomparison project results,” Journal of Hydrometeorology, vol. 7, no. 8, pp. 755–768, 2006.
- X. H. Yang, Y. N. Guo, Y. Q. Li, and L. H. Geng, “Projection pursuit hierarchy model based on chaos real-code genetic algorithm for river health assessment,” Nonlinear Science Letters C, vol. 1, no. 1, pp. 1–13, 2011.
- A. Y. Shamseldin, K. M. O'Connor, and G. C. Liang, “Methods for combining the outputs of different rainfall-runoff models,” Journal of Hydrology, vol. 197, no. 1–4, pp. 203–229, 1997.
- N. Muttil and K. W. Chau, “Neural network and genetic programming for modelling coastal algal blooms,” International Journal of Environment and Pollution, vol. 28, no. 3-4, pp. 223–238, 2006.
- A. M. Taurino, C. Distante, P. Siciliano, and L. Vasanelli, “Quantitative and qualitative analysis of VOCs mixtures by means of a microsensors array and different evaluation methods,” Sensors and Actuators B, vol. 93, no. 1–3, pp. 117–125, 2003.
- I. Vilibic and N. Leder, “Long-term variations in the Mediterranean sea level calculated by spectral analysis,” Oceanologica Acta, vol. 19, no. 6, pp. 599–607, 1996.
- D. H. Fitzpatrick and S. B. Caroline, “Spectral analysis of pressure variations during combined air and water backwash of rapid gravity filters,” Water Research, vol. 33, no. 17, pp. 3666–3672, 1999.
- P. J. Brockwell and A. D. Richard, Time Series Theory and Methods, Springer; Chep, Berlin, Germany, 2001.
- G. M. Morris, D. S. Goodsell, R. S. Halliday et al., “Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function,” Journal of Computational Chemistry, vol. 19, no. 14, pp. 1639–1662, 1998.
- K. Deb, “An efficient constraint handling method for genetic algorithms,” Computer Methods in Applied Mechanics and Engineering, vol. 186, no. 2–4, pp. 311–338, 2000.
- X. B. Hu, M. S. Leeson, and E. L. Hines, “An effective genetic algorithm for network coding,” Computers and Operations Research, vol. 39, no. 5, pp. 952–963, 2012.