Advances in Engineering Software
IEEE Expert: Intelligent Systems and Their Applications
Data mining techniques for improved WSR-88D rainfall estimation
Computers and Industrial Engineering
An application of artificial neural networks for rainfall forecasting
Mathematical and Computer Modelling: An International Journal
A nonlinear rainfall-runoff model using neural network technique: example in fractured porous media
Mathematical and Computer Modelling: An International Journal
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It is important to accurately estimate rainfall for effective use of water resources and optimal planning of water structures. For this purpose, the models were developed to estimate rainfall in Isparta using the data-mining process. The different input combinations having 1-, 2-, 3- and 4-input parameters were tried using the rainfall values of Senirkent, Uluborlu, Eğirdir, and Yalvaç stations in Isparta. The most appropriate algorithm was determined as multilinear regression among the models developed with various data-mining algorithms. The input parameters of Multilinear Regression model were the monthly rainfall values of Senirkent, Uluborlu and Eğirdir stations. The relative error of this model was calculated as 0.7%. It was shown that the data mining process can be used in estimation of missing rainfall values.