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A fuzzy method for predicting the demand for rail freight transportation

机译:铁路货运需求量的模糊预测方法

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摘要

The demand for rail freight transportation is a continuosly changing process over space and time and is affected by many quantitative and qualitative factors. In order to develop a more rational transport planning process to be followed by railway organisations, there is a need to accurately forecast freight demand under a dynamic and uncertain environment.. In conventional linear regression analysis, the deviations between the observed and the estimated values are supposed to be due to observation errors. In this paper, taking a different perspective, these deviations are regarded as the non-random uncertainties associated with forecasting issues.The details of fuzzy linear regression method are put forward and discussed in the paper. Based on an analyzes of the characteristics of the rail transportation problem, the proposed model was successfully applied to a real example from China.The results of that application are also presented here.
机译:铁路货运的需求是随时间和空间连续变化的过程,并且受许多定量和定性因素的影响。为了制定更合理的运输计划以供铁路组织遵循,需要在动态和不确定的环境下准确预测货运需求。在传统的线性回归分析中,观测值与估计值之间的偏差是应该是由于观察错误。本文从不同角度将这些偏差视为与预测问题相关的非随机不确定性。本文提出并讨论了模糊线性回归方法的细节。在分析了铁路运输问题的特征的基础上,将所提出的模型成功地应用于中国的一个实际例子中,并在此给出了应用结果。

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