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A METHOD OF DYNAMICALLY MODELLING A PAPER MANUFACTURING PLANT USING PCA (PRINCIPAL COMPONENT ANALYSIS)

机译:基于PCA的造纸厂动态建模方法(主成分分析)。

摘要

A method for converting a quantity of input data to output data of lesser dimension. A linear principal component analysis technique is applied to the input data to generate a plurality of linear principal components and an error signal. The error signal is input to a first neural network which outputs at least one variable, the said at least one variable is input to a second neural. network and the first and second neural networks are configured such that the output of the second neural network is substantially equal to the input to the first neural network. The output data is represented by the said plurality of linear principal components and the said at least one variable. There is also provided a method of dynamically modelling a paper manufacturing plant comprising derivation of a function which takes as input a plurality of parameters of said paper manufacturing plant which have been reduced in dimension and outputs a value indicative of a quality of paper output from the paper manufacturing plant.
机译:一种将大量输入数据转换为较小维度的输出数据的方法。将线性主成分分析技术应用于输入数据以生成多个线性主成分和误差信号。误差信号被输入到输出至少一个变量的第一神经网络,所述至少一个变量被输入到第二神经网络。网络和第一和第二神经网络被配置为使得第二神经网络的输出基本上等于第一神经网络的输入。输出数据由所述多个线性主分量和所述至少一个变量表示。还提供了一种动态地对造纸厂进行建模的方法,该方法包括以下函数的推导:该函数将所述造纸厂的多个参数(其尺寸已减小)作为输入,并输出表示来自造纸厂的纸张质量的值。造纸厂。

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