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Forecast of Freight Traffic of Waterways Based on Grey Model of Residual Correction

机译:基于残差修正模型的航道货运量预测

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Freight traffic of waterways is an important indicator for evaluating freight volume and the basis for decision-making management of freight traffic of waterways. Therefore, the forecast of freight traffic of waterways has important research significance. Grey system theory can make better predictions for small sample data and has a wide range of applications in the fields of economics and industrial control. Therefore, this paper intends to use the GM (1, 1) model in the grey model to predict the freight traffic of waterways. However, because a single grey prediction model has a single change rule about exponent, it is difficult to use the grey model alone to make more accurate predictions of fluctuating data such freight volume. In order to improve the prediction accuracy, the paper makes a residual correction to the model. Finally, the data of freight traffic of waterways from 2007 to 2016 is used as a sample to predict the data of 2017 and 2018 for case analysis and model verification. The research results show that the GM (1, 1) model based on the residual error correction is a suitable model and can better forecast the freight volume of water transportation.
机译:水道的货运是评估货运量的重要指标和水道货运的决策管理的基础。因此,水道的货运预测具有重要的研究意义。灰色系统理论可以更好地为小型样本数据提供更好的预测,并且在经济学和工业控制领域具有广泛的应用。因此,本文旨在在灰色模型中使用GM(1,1)模型来预测水道的货运。然而,因为单个灰色预测模型具有关于指数的单个变化规则,所以难以单独使用灰色模型来制造波动数据这种货运量的波动数据的预测。为了提高预测精度,纸张对模型进行了剩余校正。最后,从2007年到2016年的水道的货量数据被用作预测2017年和2018年数据以进行案例分析和模型验证的样本。研究结果表明,基于剩余误差校正的GM(1,1)模型是合适的模型,可以更好地预测运输的运输量。

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