Intelligent Prediction and Decision Model of Blast Furnace Temperature Based on Machine Learning and Process Control

Key Points

• Improved temperature prediction enhances blast furnace performance, leading to more efficient operations.
• The temperature control model achieved an accuracy rate of 92% in predictions during tests.
• Analysis utilized data modeling techniques including machine learning algorithms for temperature forecasting.
• This approach supports enhanced efficiency in industrial processes, indicating significant implications for operational costs.