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Application of BP Neural Network Forecast Model Based on Principal Component Analysis in Railways Freight Forecas

机译:基于主成分分析的BP神经网络预测模型在铁路货运预测中的应用

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This paper uses the BP neural network forecast model based on principal component analysis to predict China's railways freight. It firstly regroups indexes affecting railways freight by principal component analysis as to make the dimensions of index reduced and unrelated, and then it makes use of BP neural network to built model, and predicts the railways freight. The forecast result indicates that the method this paper uses has high prediction accuracy.
机译:本文使用基于主成分分析的BP神经网络预测模型来预测中国的铁路货运量。首先通过主成分分析对影响铁路货运的指标进行重组,以使指标的维数减少和不相关,然后利用BP神经网络建立模型,对铁路货运进行预测。预测结果表明本文所采用的方法具有较高的预测精度。

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