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Missing rainfall data is a frequent problem in every hydrological or water management study. Conventional methods are usually based on statistics and the missing rainfall data are estimated using neighbouring stations. The same procedure is implemented here using two models based on artificial intelligence techniques. A fuzzy logic and an Artificial Neural Network model are used to predict rainfall heights of two meteorological stations. A number of model parameters were modified during the calibration, in order to achieve the best performance. The comparison between observed and estimated values showed that both models perform satisfactorily in the prediction of rainfall data.

Rainfall data calculation using Artificial Neural Networks and adaptive neuro-fuzzy inference systems