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提出基于互信息案例推理的氧气脱碳效率预测模型,并依据预测结果计算转炉炼钢静态和动态阶段吹氧量.首先提出一种新的吹氧量预测方法,将氧气脱碳效率作为案例推理的解属性;然后将互信息引入属性权重的确定过程中,解决了传统案例检索方法忽略问题属性与解属性之间信息量的不足.将所提方法用于一座150t转炉的实际生产数据中,仿真结果表明该模型预测精度较高.该方法能够实现对转炉炼钢吹氧量的准确计算,满足实际生产的要求.
A prediction model of oxygen decarburization efficiency based on mutual information case-based reasoning is proposed, and the oxygen blowing rate in the static and dynamic stages of converter steelmaking is calculated based on the prediction results.A new oxygen blowing rate prediction method is proposed, taking the oxygen decarbonization efficiency as a case inference Then, the mutual information is introduced into the process of determining the weight of attributes, which solves the problem that the traditional case retrieval method ignores the amount of information between the problem attributes and the solution attributes.This method is applied to the actual production data of a 150t converter, The simulation results show that the model has higher prediction accuracy, which can accurately calculate the oxygen blowing capacity of converter steelmaking and meet the requirements of actual production.