The Application of Bayesian Neural Network in Rainfall Forecasting

Abstract:

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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.

Info:

Periodical:

Key Engineering Materials (Volumes 439-440)

Edited by:

Yanwen Wu

Pages:

1300-1305

DOI:

10.4028/www.scientific.net/KEM.439-440.1300

Citation:

C. J. Jiang "The Application of Bayesian Neural Network in Rainfall Forecasting ", Key Engineering Materials, Vols. 439-440, pp. 1300-1305, 2010

Online since:

June 2010

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Price:

$35.00

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