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Selecting an optimal model for forecasting the volumes of railway goods transportation

机译:选择最佳模型,用于预测铁路货物运输量

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摘要

Consideration was given to selection of an optimal model of short-term forecasting of the volumes of railway transport from the historical and exogenous time series. The historical data carry information about the transportation volumes of various goods between pairs of stations. It was assumed that the result of selecting an optimal model depends on the level of aggregation in the types of goods, departure and destination points, and time. Considered were the models of vector autoregression, integrated model of the autoregressive moving average, and a nonparametric model of histogram forecasting. Criteria for comparison of the forecasts on the basis of distances between the errors of model forecasts were proposed. They are used to analyze the models with the aim of determining the admissible requests for forecast, the actual forecast depth included.
机译:考虑了从历史和外源时间序列的铁路运输量的短期预测的最佳模型的选择。 历史数据携带有关各种货物之间的运输量的信息。 假设选择最佳模型的结果取决于商品类型,出发和目的地点的聚集水平,以及时间。 考虑是传染媒介自动增加的模型,自回归移动平均线的集成模型,以及直方图预测的非参数模型。 提出了基于模型预测误差与模型预测差距的预测比较的标准。 它们用于分析模型,目的是确定可允许的预测请求,包括实际预测深度。

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