A hybrid GA statistical method for the forecasting problem : The prediction of the river Nile inflows

The prediction of time series phenomena is a hard and complex task. Many statistical models have been used for solving such task. The selection of a proper statistical model and the setup of its parameters (in terms of the number of parameters and their values) are difficult tasks and they are usually solved by trial and error. This paper presents a hybrid system that integrates genetic algorithms -as a search algorithm- and traditional statistical models to overcome the model selection and tuning problems. The system is applied to the domain of river Nile inflows forecasting which is characterized by the availability of large amount of data and prediction models. The model sdeveloped by the proposed system are then compared with other models like traditional statistical methods and ANNs.