| Abstract |
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 |
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%. |
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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