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Ensemble pruning-based anomaly detection for improving data quality in ladle furnace temperature prediction

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Transactions of the Institute of Measurement and Control

Published online on

Abstract

Transactions of the Institute of Measurement and Control, Ahead of Print.
Molten steel temperature prediction is a crucial step in intelligent steelmaking. However, the accuracy of prediction models is often limited by low-quality industrial data, making it difficult to meet engineering requirements. To address this issue, this ...