Prediction method of blast furnace hanging based on fusion of subjective and objective evidences
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Abstract
Aiming at the difficulty of predicting blast furnace hanging, a prediction method was proposed for the hanging based on the D-S evidence theory and in combination with fuzzy expert inference and a posterior probability least squares support vector machine. Firstly, the causes of hanging are obtained by mechanism analysis in consideration of blast furnace operations and hanging phenomena. Secondly, subjective evidences are extracted by fuzzy expert reasoning, while a posterior probability least squares support vector machine model is developed to extract objective evidences. Finally, in order to predict the hanging precisely, the subjective and objective evidences are fused based on the D-S evidence theory, which makes full use of the expertise and the self-learning ability of the least squares support vector machine. Simulation results illustrate that the proposed method can make accurate prediction of the hanging.
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