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Author Turrado, Concepción Crespo ♦ López, María Del Carmen Meizoso ♦ Lasheras, Fernando Sánchez ♦ Gómez, Benigno Antonio Rodríguez ♦ Rollé, José Luis Calvo ♦ Juez, Francisco Javier de Cos
Source World Health Organization (WHO)-Global Index Medicus
Content type Text
Publisher Multidisciplinary Digital Publishing Institute
File Format HTM / HTML
Language English
Difficulty Level Medium
Subject Domain (in DDC) Computer science, information & general works ♦ Library & information sciences ♦ Natural sciences & mathematics ♦ Life sciences; biology ♦ Physiology & related subjects ♦ Technology ♦ Medicine & health ♦ Human physiology ♦ Diseases ♦ Manufacture for specific uses ♦ Precision instruments & other devices
Subject Domain (in MeSH) Investigative Techniques ♦ Analytical, Diagnostic and Therapeutic Techniques and Equipment ♦ Physical Phenomena ♦ Biological Phenomena ♦ Biological Sciences ♦ Information Science ♦ Information Science
Subject Keyword Discipline Biotechnology ♦ Artifacts ♦ Atmosphere ♦ Analysis ♦ Models, Statistical ♦ Radiometry ♦ Methods ♦ Sample Size ♦ Solar Energy ♦ Statistics & Numerical Data ♦ Computer Simulation ♦ Data Interpretation, Statistical ♦ Multivariate Analysis ♦ Radiation Dosage ♦ Reproducibility Of Results ♦ Sensitivity And Specificity ♦ Journal Article ♦ Research Support, Non-u.s. Gov't
Abstract Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.
Description Country affiliation: Spain
Author Affiliation: Turrado CC ( Maintenance Department, University of Oviedo, San Francisco 3, Oviedo 3307, Spain.; López Mdel C ( Departamento de Ingeniería Industrial, University of A Coruña, A Coruña 15405, Spain.; Lasheras FS ( Department of Construction and Manufacturing Engineering, University of Oviedo, Gijón 33204, Spain.; Gómez BA ( Departamento de Ingeniería Industrial, University of A Coruña, A Coruña 15405, Spain.; Rollé JL ( Departamento de Ingeniería Industrial, University of A Coruña, A Coruña 15405, Spain.; Juez FJ ( Project Management Area, Mining Department, University of Oviedo, Oviedo 33004, Spain.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Reading ♦ Research ♦ Self Learning
Interactivity Type Expositive
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-10-29
Publisher Place Switzerland
e-ISSN 14248220
Journal Sensors
Volume Number 14
Issue Number 11

Source: WHO-Global Index Medicus