Monthly Rainfall Estimation Using Data-Mining Process
Author
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-30
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Terzi, Özlem. 2012. Monthly Rainfall Estimation Using Data-Mining Process. Applied Computational Intelligence and Soft Computing،Vol. 2012, no. 2012, pp.1-6.
https://search.emarefa.net/detail/BIM-491508
Modern Language Association (MLA)
Terzi, Özlem. Monthly Rainfall Estimation Using Data-Mining Process. Applied Computational Intelligence and Soft Computing No. 2012 (2012), pp.1-6.
https://search.emarefa.net/detail/BIM-491508
American Medical Association (AMA)
Terzi, Özlem. Monthly Rainfall Estimation Using Data-Mining Process. Applied Computational Intelligence and Soft Computing. 2012. Vol. 2012, no. 2012, pp.1-6.
https://search.emarefa.net/detail/BIM-491508
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-491508