1 citations · 1 across the 8 of their papers we have counts for
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Segmentation over Complexity: Evaluating Ensemble and Hybrid Approaches for Anomaly Detection in Industrial Time Series
Emilio Mastriani, Alessandro Costa, Federico Incardona +2
In this study, we investigate the effectiveness of advanced feature engineering and hybrid model architectures for anomaly detection in a multivariate industrial time series, focus…
Improving Anomaly Detection in Industrial Time Series: The Role of Segmentation and Heterogeneous Ensemble
Emilio Mastriani, Alessandro Costa, Federico Incardona +2
Concerning machine learning, segmentation models can identify state changes within time series, facilitating the detection of transitions between normal and anomalous conditions. S…
Predictive Maintenance Study for High-Pressure Industrial Compressors: Hybrid Clustering Models
Alessandro Costa, Emilio Mastriani, Federico Incardona +2
This study introduces a predictive maintenance strategy for high pressure industrial compressors using sensor data and features derived from unsupervised clustering integrated into…