The Application of Bayesian Neural Network in Rainfall Forecasting

Abstract:

The process of Rainfall Forecasting very complex and highly nonlinear and exhibits both temporal and spatial variability’s, In this article, a Rainfall Forecasting model using the Bayesian neural networks (BNN) is proposed for Rainfall Forecasting. The study uses the data from a coastal forest catchment. This article studies the accuracy of the short-term rainfall forecast obtained by BNN time-series analysis techniques and using antecedent rainfall depths and stream flow as the input information. The verification results from the proposed model indicate that the approach of BNN Rainfall Forecasting model presented in this paper shows a reasonable agreement in Rainfall Forecasting modeling with high accuracy.

• Periodical: Key Engineering Materials (Volumes 439-440)
• Pages: 1300-1305
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.439-440.1300
• Online since: June 2010
• Authors: Chuan Jin Jiang
• Keywords: Bayesian Neural Network, Forecasting Model, Rainfall Forecasting

References

[1] G.F. Lin, L.H. Chen. A nonlinear rainfall-runoff model using radial function network. Journal of Hydrology, 289: 1-8, (2004).

[2] Kin. C. L, J. E. Ball and A. Sharma. An Application of Artificial Neural Networks for Rainfall Forecasting. Mathematical and Computer Modelling, 33: 683-693, (2001).

DOI: 10.1016/s0895-7177(00)00272-7

[3] BoyKo. Dodov, Efi. Foufoula-Georgiou. Incorporating the spatio-temporal distribution of rainfall and basin geomorphology into nonlinear analyses of streamflow dynamics. Advances in Water Resources, 28: 711-728, (2005).

DOI: 10.1016/j.advwatres.2004.12.013

[4] J. S. Wu. Forecast research and applying of bp neural network based on genetic algorithms. Mathematics in Practice and Theory, 65(24): 665-680, (2004).

[5] Robert. J. M, Victoria. A. B, David A. Jone. Forecasting for flood warning. Comptes Rendus Geoscience, 337: 203-217, (2005).

DOI: 10.1016/j.crte.2004.10.017

[6] Govindaraju. R. S. Artificial neural network in hydrology, I: Preliminary concepts. Journal of Hydrologic Engineering, 5(2): 115-123, (2000).

[7] M.N. French, W.F. Krajewski, R.R. Cuykendall. Rainfall forecasting in space and time using a neural network. Journal of Hydrology, 137(1-): 1-31, (1992).

DOI: 10.1016/0022-1694(92)90046-x

[8] K.C. Luk, J.E. Ball and A. Sharma. A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting. Journal of Hydrology, 227(1-4): 56-65, (2000).

DOI: 10.1016/s0022-1694(99)00165-1

[9] Bishop. CM. Neural networks for pattern recognition. Oxford: Oxford University Press, (1995).

[10] L. Breiman. Combining Predictors. Proceedings of Combining Artificial Neural Nets-Ensemble and Modular Multi-net Systems, the Springer Press, Berlin, 1: 31-50, (1999).

[11] J. A. Benediktsson, J. RSveinsson, O. K. Ersoy and P. H. Swain. Parallel Consensual Neural Neural Networks. IEEE Transactions on Neural Networks, 8: 54-64, (1997).

DOI: 10.1109/72.554191

[12] Malakoff. DM. Bayes offer new way to make sense of numbers. Science, 286: 1460-1464, (1999).

DOI: 10.1126/science.286.5444.1460

[13] Cox. RT. Probability, frequency and reasonable expectation. American Journal of Physics, 14: 1-13, (1946).

[14] Yuanchang. Xie, Dominique. Lord, Yunlong. Zhang, Predicting motor vehicle collisions using Bayesian neural network models: An empirical analysis. Accident Analysis and Prevention 39: 922-933, (2007).

DOI: 10.1016/j.aap.2006.12.014

[15] Philippe. Lauret, Eric. Fock, Rija. N. Randrianarivony, Bayesian neural network approach to short time load forecasting. Energy Conversion and Management, 49: 1156-1166, (2008).

DOI: 10.1016/j.enconman.2007.09.009

[16] Wei-Chiang. Hong. Rainfall forecasting by technological machine learning models. Applied Mathematics and Computation, 200: 41-57, (2008).

DOI: 10.1016/j.amc.2007.10.046

[17] J. S. Wu. Forecast research and applying of bp neural network based on genetic algorithms. Mathematics in Practice and Theory, 65(24): 665-680, (2004).

[18] Jiansheng Wu, Long Jin. Neural Network with Partial Least Square Prediction Model Based on SSA-MGF. Journal of Catastrophology, 21(2): 17-23, (2006).

DOI: 10.1109/wcica.2006.1712870