本文提出了一种新的基于神经网络软测量模型及算法，为复杂测量系统中软测量建模提供了一种有效的途径。

This paper introduces a new model and algorithm of soft measurement based on Neural Network. It can solve the problem of soft measurement modeling in complicated.

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利用软测量的思想，采用神经网络建立软测量模型和小波分析进行数据处理，以克服传统方法的不足，提高出口带钢厚度预测的精度。

The idea of soft-measurement is used in our work and neural network and wavelet transform are adopted to overcome deficiency of traditional method and improve forecast accuracy of exit thickness.

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本文采用主成分分析技术对过程数据降维，然后用降维后的数据训练神经网络，建立软测量模型。

Then, USES PCA to reduce the dimensions of process data, trains the neural network with that data, and establishes the soft sensor.

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