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Abstract
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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
Submitted: February 02, 2012
Accepted: March 02, 2012
Published: November 01, 2012 |
Abstract:
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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%.
Key words: Artificial neural networks, discharge, forecasting, river Kaduna, water resources, ,
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Cite this Reference:
J.O. Folorunsho, E.O. Iguisi, M.B. Mu’azu and S. Garba, . Development of an ANN-Based Model for Forecasting River Kaduna Discharge. Research Journal of Applied Sciences, Engineering and Technology, (21): 4284-4292.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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