Detecting Outliers in Electric Arc Furnace under the Condition of Unlabeled, Imbalanced, Non-stationary and Noisy Data
The presence of outliers is the main reason leading to ineffectiveness of advanced data-driven control methods in electric arc furnace systems. This paper proposes a hybrid method dedicated to detecting outliers in electric arc furnace systems, where process data are characterized as unlabeled, imba...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2018-04-01
|
| Series: | Measurement + Control |
| Online Access: | https://doi.org/10.1177/0020294018771097 |