Application of Knowledge Discovery in Databases in Evapotranspiration Estimation: an Experiment in the State of Rio de Janeiro

Authors

Fernando Xavier, Universidade Federal do Estado do Rio de Janeiro (UNIRIO)Follow
Asterio Kiyoshi Tanaka, Universidade Federal do Estado do Rio de Janeiro (UNIRIO)Follow
Kate Cerqueira Revoredo, Universidade Federal do Estado do Rio de Janeiro (UNIRIO)Follow

Document Type

Article

Publication Date

5-2015

Keywords

KDD, Data Mining, Hydrology, Evapotranspiration, Linear Regression

Abstract

With the growing volume of data in various areas such as Hydrology, there is a need for using information systems to aid in handling such data. This article is a report of an experiment that used knowledge discovery techniques to estimate an important component of the hydrological cycle: evapotranspiration. The experiment reported in this article was done with weather data and showed that some algorithms, such as M5P, present good results when compared to historical data of the estimated evapotranspiration.

Comments

This paper is in Portuguese (Aplicação de Descoberta de Conhecimento em Bases de Dados na Estimativa da Evapotranspiração: um Experimento no Estado do Rio de Janeiro)

Recommended Citation

Xavier, Fernando; Tanaka, Asterio Kiyoshi; and Revoredo, Kate Cerqueira, "Application of Knowledge Discovery in Databases in Evapotranspiration Estimation: an Experiment in the State of Rio de Janeiro" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 76.
https://aisel.aisnet.org/sbis2015/76