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OALib Journal期刊
ISSN: 2333-9721
费用：99美元
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基于分类回归树的高炉铁水硅含量预测模型
, PP. 548-552
Keywords: 铁水硅含量,分类回归树,支持向量机
Abstract:
针对高炉铁水硅含量的预测问题,作者探索出基于分类回归树算法的建模策略,为高炉炉温控制提供了新的可选思路.针对某高炉的在线生产数据,分别建立了分类回归树预测模型和支持向量机预测模型,并从命中率、均方根误差对模型的性能进行了分析.结果表明:分类回归树模型的预测精度整体优于支持向量机模型,尤其在炉况波动较大时预测效果较好.
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