Prediction of oxygen decarburization efficiency based on mutual information case-based reasoning

  • Authors:

  • Min Han;Liwen Jiang

  • Affiliations:

  • School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, China

  • Venue:
  • ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
  • Year:
  • 2011

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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.