Abstract
Oxygen decarburization efficiency prediction model based on mutual information case-based reasoning is proposed and the blowing oxygen of static and dynamic phases is calculated according to the forecasting results. First, a new prediction method of blowing oxygen is proposed which attributes the oxygen decarburization efficiency as solution properties of case-based reasoning. Then the mutual information is introduced into the process of determining weights of attributes, which solve the problem that the lack of information is ignored between the problem properties and the solution property in the traditional case retrieval method. The proposed model will be used in a 150 tons converter for the actual production data. The results show that the model has high prediction accuracy. On this basis the calculation accuracy of blowing oxygen in the two phases is ensured and the requirements of actual production are met.
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© 2011 Springer-Verlag Berlin Heidelberg
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Han, M., Jiang, L. (2011). Prediction of Oxygen Decarburization Efficiency Based on Mutual Information Case-Based Reasoning. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21111-9_35
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DOI: https://doi.org/10.1007/978-3-642-21111-9_35
Publisher Name: Springer, Berlin, Heidelberg
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