RT Journal Article
T1 Benchmarking anomaly detection methods: Insights from the UCR Time Series Anomaly Archive
A1 Baldán, Francisco J.
A1 García-Gil, Diego
K1 Series temporales
K1 Análisis de series temporales
K1 Aplicaciones informáticas
AB Anomaly detection, vital for identifying deviations from normative data patterns, is particularly crucial in sensor-driven real-world applications, which predominantly involve temporal data in the form of time series. Traditional evaluation of anomaly detection methods has relied on public benchmark datasets. Yet, recent revelations have uncovered inherent flaws and inadequacies in these datasets, casting doubt on the perceived progress in the field. To address this challenge, the UCR Time Series Anomaly Archive has been recently proposed—a meticulously curated database comprising 250 time series—designed to provide a robust and error-free benchmark for anomaly detection research. This paper comprehensively evaluates state-of-the-art anomaly detection techniques using the UCR Time Series Anomaly Archive. Our findings demonstrate the efficacy of current methods in accurately detecting anomalies across an important portion of datasets without additional optimization, underscoring the archive's utility as a foundational baseline for future research and development in anomaly detection methodologies.
PB Wiley
YR 2025
FD 2025-02
LK https://hdl.handle.net/10630/36084
UL https://hdl.handle.net/10630/36084
LA eng
NO Baldán, F. J., & García‐Gil, D. (2025). Benchmarking Anomaly Detection Methods: Insights From the UCR Time Series Anomaly Archive. Expert Systems, 42(2), e13767.
NO Funding for open access charge: Universidad de Málaga / CBUA.This work was supported by Grant FJC2021-047112-I funded by MICIU/AEI/10.13039/501100011033 and by European Union Next Generation EU/PRTR. Spanish Ministry of Science and Innovation under project TED2021-132702B-C21 funded by MCIN/AEI/10.13039/501100011033 “European Union PRTR” PID2020-119478GB-I00.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026