Sinter Quality Prediction Based on Parallel Genetic Algorithms
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DOI: 10.23977/icamcs2019.69
Author(s)
Liu Guangyue, Hu Qinghe, Zhang Shuang
Corresponding Author
Liu Guangyue
ABSTRACT
In the experiment of measuring assimilation and flowability of iron ore powder, different methods are used in this paper. This method takes into account the information of reaction process synthetically, that is, the evaluation index is defined based on multi-factor consideration, so the description of iron ore powder is more comprehensive. Although there are many methods to guide ore blending, the task of sintering cup experiment to verify the ore blending scheme is still very large. The method used in this paper to determine the assimilation and fluidity of iron ore powder can provide a preliminary prediction of the metallurgical properties of sinter and reduce some unnecessary sintering cup experiments and droplet experiments.
KEYWORDS
Genetic algorithm, quantum parallel, sinter quality, prediction