基于类别映射的编组站车辆中时预测模型
Forecast model of wagon operation time in marshalling station based on category mapping

摘要 现行铁路编组站车辆中时预测方法不能满足实际运输组织需求，结合车辆中时数据平稳性特点，设计基于类别映射的货种与车种映射函数，充分考虑车种别、货种别车辆中转作业差异，重新生成车辆中时序列.采用时间序列分析方法分析中时序列，提出新的编组站车辆中时预测模型，并采用极大似然估计法对参数进行估计并求解模型.实验结果表明，该方法能够较准确预测编组站车辆中时，符合实际中时发展趋势，提高了铁路车流预测的准确性.
Abstract：The contemporary railway marshalling station wagon forecast method cannot meet the requirements compared with the actual railway transport organization. Combined with the characteristics of the stability of the wagon operation time data, the goods-wagon type mapping function is designed. Considering the impact of the difference between the wagon type and the goods type, the new time series is dynamic updated. A new forecasting model of marshalling yard wagon transit operation is put forward with time series analysis method. The parameters in the model are estimated using the maximum likelihood estimate method. The experimental results indicate that the proposed model is conducive to forecast and analyze the transportation organization activities, could accurately forecast the wagon transit time, conform to the actual development trend and improve the accuracy of railway traffic flow forecast.