首页> 外文会议>International conference on electronic measurement instruments;ICEMI' 2009 >A Novel Model Variable Selection Method Based on Energy Variation and Its Application to Predictive Modeling for Achromic Power
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A Novel Model Variable Selection Method Based on Energy Variation and Its Application to Predictive Modeling for Achromic Power

机译:基于能量变化的模型变量选择新方法及其在无色功率预测建模中的应用

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Achmoric power, one of the most important quality indices in a Lithopone calcination process, cannot be measured online economically, which is a similar problem many rotary kiln processes encounter. This paper talks about its predictive model by applying data modeling technique and focuses on the model variable selection. According to the Lithopone calcination mechanism, several schemes of model variable selection are discussed, and the one based on energy variation which mixes the information of calcinating temperature and calcinating duration together is chosen at last. To calculate the energy absorbed by the material, "Unit Energy" is introduced, which offers a convenient expression in the form of relative value. Using this novel model variable selection method, the model structure is simplified, which has an advantage in model efficiency. A predictive model for achmoric power is obtained in the next step by least square support vector machines method, and the simulation result shows its promising performance.
机译:立陶宛煅烧过程中最重要的质量指标之一,手抄本功率不能在线经济地测量,这是许多回转窑工艺遇到的类似问题。本文通过应用数据建模技术讨论其预测模型,并着重于模型变量的选择。根据立陶宛煅烧机理,讨论了几种模型变量选择方案,最后选择了一种基于能量变化的模型,将煅烧温度和煅烧时间信息混合在一起。为了计算材料吸收的能量,引入了“单位能量”,它以相对值的形式提供了一种方便的表达方式。使用这种新颖的模型变量选择方法,简化了模型结构,在模型效率方面具有优势。下一步通过最小二乘支持向量机方法获得非手术能力的预测模型,仿真结果表明该方法具有良好的应用前景。

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