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This study developed a neurofuzzy-based rainfall-runoff forecast model for river basin and evaluated the performance of the model. This was with a view to capturing the behaviour of hydrological and meterological variables involved in rainfall-runoff process to improve forecast accuracy of rainfallrunoff. Three hydrological variables were used for model development. Also, a three-layered feedforward model was developed using the same input variables in comparison with the neurofuzzy-based model. The simulation was done using MATLAB® 7.0. The simulation results showed that neurofuzzy-based model has higher coefficient of determination (R2) and lower root mean square error (RMSE) over the threelayered feedforward model.This study concluded that the neurofuzzy-based model improved the forecast accuracy of the rainfall-runoff of Benin-Owena river basin better than three-layered feedforward model using the same hydrological conditions.
Oyebode et al. (Thu,) studied this question.
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