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Detección de anómalos en series de tiempo

Authors: López González-Valerio, Luis;

Detección de anómalos en series de tiempo

Abstract

[Resumen]: La detección de valores atípicos en series de tiempo constituye una tarea de gran relevancia para asegurar la validez y la fiabilidad de los análisis. En el presente trabajo se lleva a cabo una evaluación, a través de diferentes escenarios de simulación, de múltiples combinaciones de algoritmos de detección de valores atípicos en series temporales.Este estudio de simulación posibilita la identificación de los métodos más eficientes y proporciona una base sólida para el análisis de la presencia de valores atípicos en series de tiempo con datos reales.

[Abstract]: The detection of outliers in time series constitutes a task of great importance to ensure the validity and reliability of analyses. In this study, an evaluation is carried out, through different simulation scenarios, of multiple combinations of algorithms for outlier detection in time series. This simulation study enables the identification of the most efficient methods and provides a solid foundation for the analysis of the presence of outliers in time series with real data.

Traballo fin de grao (UDC.FIC). Ciencia e enxeñaría de datos. Curso 2024/2025

Country
Spain
Related Organizations
Keywords

Modelos ARIMA, Outlier detection in time series, Evaluation metrics, Time series modeling, Detección de atípicos en series temporales, Métricas de evaluación, Modelización de series de tiempo, ARIMA Models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green