Abstract
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.
Highlights
The meteorological events affect permanently human life
Considering the meteorological phenomena, which have no possibility of intervention, they cause the important results in human life, accurate estimation and analysis of these variables are very important
Rainfall estimation is very important in terms of effects on human life, water resources, and water usage areas
Summary
The meteorological events affect permanently human life. Considering the meteorological phenomena, which have no possibility of intervention, they cause the important results in human life, accurate estimation and analysis of these variables are very important. Partal et al [8] developed rainfall estimation models using artificial neural networks and wavelet transform methods. Chang et al [10] applied a modified method, combining the inverse distance method and fuzzy theory, to precipitation interpolation They used genetic algorithm to determine the parameters of fuzzy membership functions, which represent the relationship between the location without rainfall records and its surrounding rainfall gauges. Teegavarapu and Chandramouli [6] developed a model that uses artificial neural network concepts and a stochastic interpolation technique. They tested the model for estimation of missing precipitation data. The aim of the study is to evaluate the use of data-mining process to estimate rainfall of Isparta in Turkey. This study is performed using rainfall data of Senirkent, Uluborlu, Egirdir, and Yalvacstations in Isparta city
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