Open AccessGenetic Programming and Standardization in Water Temperature Modelling
Author(s) -
Maritza Liliana Arganis Juárez,
Rafael GonzálezVal,
Jordi Prats,
Katya Rodríguez,
Ramón Domínguez,
Josep Dolz
Publication year - 2009
Publication title -
advances in civil engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.379
H-Index - 25
eISSN - 1687-8094
pISSN - 1687-8086
DOI - 10.1155/2009/353960
Subject(s) - standardization , genetic programming , variance (accounting) , computer science , genetic algorithm , explanatory power , mean squared error , mean squared prediction error , order (exchange) , statistics , data mining , machine learning , mathematics , philosophy , accounting , epistemology , business , operating system , finance , economics
An application of Genetic Programming (an evolutionary computational tool) without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes
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