- 期刊
- OpenAccess
Development of an ANN-Based Model for Forecasting River Kaduna Discharge
並列摘要
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%.