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Machine Learning-Based Soft Sensors for Vacuum Distillation Unit
Firstly, it is important to enhance the quality of both sets of data (laboratory measurements and physical sensors) in a data pre-processing stage (as described in Methodology section).
Pre-treatment of outliers and anomalies in plant data: Methodology and case study of a Vacuum Distillation Unit
In this case, we used principal component analysis (PCA) with Hotelling's $T^2$ statistics to identify the long-term outliers.
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