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A Multi-scale Modeling Method Based on Big Data

机译:基于大数据的多尺度建模方法

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A multi-scale modeling method based on big data was proposed to establish neural network models for complex plant. Wavelet transform was used to decompose input and output parameters into different scales. The relationship between these parameters were researched in every scale. Then models in each scale were established and added together to form a multi-scale model. A model of coal mill current in power plant was established using the multi-scale modeling method based on big data. The result shows that, the method is effective.
机译:提出了一种基于大数据的多尺度建模方法,为复杂植物建立神经网络模型。小波变换用于将输入和输出参数分解为不同的尺度。这些参数之间的关系在每个规模中都研究过。然后建立每个刻度中的模型,并将其添加在一起以形成多尺度模型。基于大数据的多尺度建模方法建立了发电厂煤轧机电流模型。结果表明,该方法是有效的。

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