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2012 (Vol. 4, Issue: 21)
Article Information:

Development of an ANN-Based Model for Forecasting River Kaduna Discharge

J.O. Folorunsho, E.O. Iguisi, M.B. Mu’azu and S. Garba
Corresponding Author:  J.O. Folorunsho 

Key words:  Artificial neural networks, discharge, forecasting, river Kaduna, water resources, ,
Vol. 4 , (21): 4284-4292
Submitted Accepted Published
February 02, 2012 March 02, 2012 November 01, 2012
Abstract:

Artificial Neural Networks (ANNs) provides a quick and flexible means of creating models for river discharge forecasting and has been shown to perform well in comparison with conventional methods. This paper presents a method of discharge prediction for River Kaduna by developing an ANN-based model. Given the major triple problems of unavailability, inconsistency and paucity of data, the water resources planning and development in any drainage basin always suffer a setback. Rainfall, temperature, relative humidity and the stage height (input variables) and discharge (target output) data were obtained for River Kaduna drainage basin for April-October 1975 to 2004. In order to develop the ANN model, the data set was partitioned into two parts of 24 months sets. 70% of the entire data was used as training data and 30% of the entire data used as the validation data. From the results obtained, the developed Artificial Neural Network (ANN) model developed in the PredictDemo NeuralWare Environment using the Neural Statistics shows a correlation value of 82%.
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  Cite this Reference:
J.O. Folorunsho, E.O. Iguisi, M.B. Mu’azu and S. Garba, 2012. Development of an ANN-Based Model for Forecasting River Kaduna Discharge.  Research Journal of Applied Sciences, Engineering and Technology, 4(21): 4284-4292.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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