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Computación y Sistemas
versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546
Comp. y Sist. vol.7 no.1 Ciudad de México Jul./Set. 2003
Artículo
Recognition of system behaviours based on temporal series similarity
D. Llanos1, F.J. Cuberos2, J. Meléndez1, Fco. I. Gamero1, J. Colomer1 and J.A. Ortega3
1 Grupo eXiT, University of Girona. Av. Lluis Santalo s/n E17071Girona (Spain) dllanosr@eia.udg.es ; quimmel@eia.udg.es ; gamero@eia.udg.es ; colomer@eia.udg.es
2 Departamento de Planificación. Radio Televisión de Andalucía. Crta. San JuanTomare km. 1,3. S.J. AznalfaracheSevilla (Spain) fcuberos@rtva.es
3 Departamento de Lenguajes y Sistemas Informáticos. University of Seville. Avda Reina Mercedes S/n. Sevilla (Spain) ortega@lsi.us.es
Resumen
Existen multitud de aproximaciones al estudio de los sistemas que evolucionan en el tiempo. Este artículo revisa trabajos previos relacionados con series temporales y evalúa tres aproximaciones enfocadas a la comparación de dicho tipo de series. Dos aproximaciones están basadas en los principios del algoritmo Dynamic Time Warping (DTW) y una de ellas usa representación cualitativa basada en sodios. Ambas estrategias son discutidas y aplicadas en la diagnosis de un sistema de tanques y en la recuperación de registros de perturbaciones obtenidos en una subestación de distribución eléctrica. La tercera aproximación usa un índice de similitud definido por etiquetas cualitativas. Cada etiqueta representa un rango de valores que, desde una perspectiva cualitativa, podemos considerar similares. Esta aproximación se prueba con dos conjuntos de datos. Este estudio se completa con un estudio del ruido y de otros posibles etiquetados.
Palabras clave: Series Temporales, Análisis de series temporales, Análisis Cualitativo, Programación Dinámica, Formas, Conocimiento Cualitativo, Ruido.
Abstract
There are different approaches to the temporal study of time evolving systems. This paper reviews previous works related to time series and it evaluates three approaches focused to the comparison of these type of series. Two approaches are based on the principles of Dynamic Time Warping algorithm (DTW) and one of them uses qualitative representation based on episodes. Both strategies are discussed and applied to a tank system diagnosis and retrieval of registers of perturbations gathered in a electric distribution substation. The third approach uses a similarity index defined by qualitative labels. Each label represents a range of values that, from a qualitative perspective, we may consider similar. This approach is tested with two datasets. This study is completed with a evaluation of noise and other possible labellings.
Keywords: Temporal series, Timeseries Analysis, Qualitative Analysis, Dynamic Programming, Shapes, Qualitative Knowledge, Noise.
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Acknowledgement
This work is partially supported by the projects "Desarrollo de un sistema de control y supervisión aplicado a un reactor secuencial por cargas para la eliminación de materia orgánica, nitrógeno y Fósforo" (DPI200204579C0201) and DPI SECSE "Supervisión Experta de la Calidad de Servicio Eléctrico" (DPI20012198) within the CICYT program from the Spanish government and FEDER funds.
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