| 基于支持向量机的连铸板坯表面温度预测 |
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| 引用本文： | 舒服华,丁剑刚.基于支持向量机的连铸板坯表面温度预测[J].炼钢,2009,25(1). |
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| 作者姓名： | 舒服华 丁剑刚 |
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| 作者单位： | 1. 武汉理工大学,机电工程学院,湖北,武汉,430074
2. 大冶钢铁公司,板材厂,湖北,黄石,435102 |
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| 摘 要： | 提出了一种最小二乘支持向量机的连铸板坯表面温度预测新模型.以中间罐温度、拉速、二冷水量等主要工艺因素为输入,连铸坯表面温度为输出,通过最小二乘支持向量机模型拟合输入与输出之间的复杂非线性函数关系.以现场采集的连铸生产工艺数据为样本对模型进行学习训练,用训练好的模型预测在一定工艺条件下板坯的表面温度.实践表明该方法具有建模速度快、预测精度高、操作简便等优点,不仅克服了常规的BP预测模型的不足,而且性能优于标准支持向量机预测模型.
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| 关 键 词： | 连铸板坯 表面温度 预测模型 最小二乘支持向量机 |
A slab surface temperature prediction model based on least square support vector machine |
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| SHU Fu-hua,DING Jian-gang.A slab surface temperature prediction model based on least square support vector machine[J].Steelmaking,2009,25(1). |
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| Authors: | SHU Fu-hua DING Jian-gang |
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| Affiliation: | 1.School of Mechanical and Electronic Engineering;Wuhan University of Technology;Wuhan 430074;China;2.Steel Sheet Mill of Daye Iron and Steel Company;Huangshi 435102;China |
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| Abstract: | Based on least square support vector machine(LS-SVM) a novel slab surface temperature prediction model was proposed.With a few main processing parameters such as the tundish temperature,drawing speed and volume of the secondary cooling water as inputs,the slab surface temperature as output,the complicated non-linear functional relation between input and output is derived by means of the LS-SVM based model.The new model was repeatedly practised for training purpose using the on-site collected continuous cast... |
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| Keywords: | continuous cast slab surface temperature prediction model least square support vector machine |
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