首页|Ladle Furnace Temperature Prediction Model Based on Large-scale Data With Random Forest
Ladle Furnace Temperature Prediction Model Based on Large-scale Data With Random Forest
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国家科技期刊平台
NETL
NSTL
万方数据
维普
In ladle furnace, the prediction of the liquid steel temperature is always a hot topic for the researchers. The most of the existing temperature prediction models use small sample set. Today, the precision of them can not satisfy practical production. Fortunately, the large sample set is accumulated from the practical production process. However, a large sample set makes it difficult to build a liquid steel temperature model. To deal with the issue, the random forest method is preferred in this paper, which is a powerful regression method with low complexity and can be designed very quickly. It is with the parallel ensemble structure, uses sample subsets, and employs a simple learning algorithm of sub-models. Then, the random forest method is applied to establish a temperature model by using the data sampled from the production process. The experiments show that the random forest temperature model is more precise than other temperature models.
国家科技期刊平台
NSTL
万方数据
维普
