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Monthly Rainfall Estimation Using Data-Mining Process
Author(s) -
Özlem Terzi
Publication year - 2012
Publication title -
applied computational intelligence and soft computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 10
eISSN - 1687-9732
pISSN - 1687-9724
DOI - 10.1155/2012/698071
Subject(s) - multilinear map , computer science , process (computing) , estimation , data mining , regression , statistics , mathematics , management , pure mathematics , economics , operating system
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.

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