A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance

Research article (International Journal of Data Science and Analytics, 2021) · cited 24× · AI/ML
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A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance

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A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-unsupervised-method-for-anomaly-detection-in-time-series-based-on-statistical-features-for-industrial-predictive
MLA “A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-unsupervised-method-for-anomaly-detection-in-time-series-based-on-statistical-features-for-industrial-predictive.
BibTeX @misc{4ortxyz_a-novel-unsupervised-method-for-anomaly-detection-in-time-series-based-on-statistical-features-for-industrial-predictive_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel unsupervised method for anomaly detection in time series based on statistical features for industrial predictive maintenance}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-unsupervised-method-for-anomaly-detection-in-time-series-based-on-statistical-features-for-industrial-predictive}, note = {Accessed: 2026-05-24}}
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