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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/40261

Title: Hybrid algorithm for missing data imputation and its application to electrical data loggers
Author(s): Crespo Turrado, María Concepción
Sánchez Lasheras, Fernando
Calvo Rolle, José Luis
Piñón-Pazos, A.-J.
García Melero, Manuel Emilio
Cos Juez, Francisco Javier de
Keywords: Missing data imputation
Multivariate imputation by chained equations (MICE)
Mahalanobis distances
Self-Organized Maps Neural Networks (SOM)
Issue date: 2016
Publisher: MDPI
Publisher version: http://dx.doi.org/10.3390/s16091467
Citation: Sensors (Switzerland), 16(9), p. 1467- (2016); doi:10.3390/s16091467
Format extent: p. 1467-
Abstract: The storage of data is a key process in the study of electrical power networks related to the search for harmonics and the finding of a lack of balance among phases. The presence of missing data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, current in each phase and power factor) affects any time series study in a negative way that has to be addressed. When this occurs, missing data imputation algorithms are required. These algorithms are able to substitute the data that are missing for estimated values. This research presents a new algorithm for the missing data imputation method based on Self-Organized Maps Neural Networks and Mahalanobis distances and compares it not only with a well-known technique called Multivariate Imputation by Chained Equations (MICE) but also with an algorithm previously proposed by the authors called Adaptive Assignation Algorithm (AAA). The results obtained demonstrate how the proposed method outperforms both algorithms
URI: http://hdl.handle.net/10651/40261
ISSN: 1424-8220
Sponsored: Francisco Javier de Cos Juez and Fernando Sánchez Lasheras appreciate support from the Spanish Economics and Competitiveness Ministry, through grant AYA2014-57648-P and the Government of the Principality of Asturias (Consejería de Economía y Empleo), through grant FC-15-GRUPIN14-017
Project id.: AYA2014-57648-P
FC-15-GRUPIN14-017
Appears in Collections:Artículos
Ingeniería Eléctrica, Electrónica, de Computadores y Sistemas
Investigaciones y Documentos OpenAIRE

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