Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/69781
Título: An approach for multiparameter meteorological forecasts
Autores/as: Pérez-Vega, Abrahán
Travieso-González, Carlos M. 
Hernández-Travieso, José Gustavo
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Meteorology
Prediction
Multiparameter forecasting
Regression tree
Fit linear model
Fecha de publicación: 2018
Proyectos: Generacion de Un Marco Unificado Para El Desarrollo de Patrones Biometricos de Comportamiento 
Publicación seriada: Applied Sciences (Basel) 
Resumen: Accurate meteorological forecasting has great importance in different fields. This works introduces a system to obtain precise predictions, which uses regression functions, and collected data using the meteorological stations from the Gran Canaria and South Tenerife airports. The dataset offers information about different phenomena as temperature, wind speed, solar radiation, pressure, moisture, cloudiness, rainfall and meteors. A preprocessing stage has been applied before prediction stage to adapt the collected data. A support vector machine, regression tree, and fit linear model are applied as regression functions. Results has been measured by the mean square error. These results reached an accuracy of 0.07 °C for temperature, 0.56 km/h for wind speed, 7.45 tenths of kJ/m2 for solar radiation and 0.11 mm for precipitation. It shows the robustness of the multiparameter meteorological forecast approach.
URI: http://hdl.handle.net/10553/69781
ISSN: 2076-3417
DOI: 10.3390/app8112292
Fuente: Applied Sciences [ISSN 2076-3417], v. 8 (11), 2292
Colección:Artículos
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