摘要
针对传统的GM(1,N)模型在进行货运量预测时存在误差较大的情况,应用等维灰度递补的思想,通过对传统GM(1,N)模型进行改进,将新的预测数据替换最初的数据,提出一种改进的GM(1,N)模型。通过2种模型预测结果的对比分析可以看出:改进的GM(1,N)模型在预测精度方面较传统的GM(1,N)模型有大幅度提高。该模型能够更加及时、准确地反映数据的变化,且计算简便、精度较好,在货运量预测领域有着较高的实用及研究价值。
In order to minis the excessive error from traditional GM（1,N） mode in freight volume forecasting, this paper uses the idea of equal-dimension gray filling to improve the traditional GM（1,N） mode. Meanwhile, using the new forecast data to replace the original data, this paper proposes an improved GM （1, N） model. Through a comparative analysis of the results of the two models can be seen that improved GM （1, N） model in forecasting accuracy has been significantly improved than traditional GM （1, N） model. This model can be more timely and accurate reflection of changes in the data. This model, with simple calculation and higher accuracy, has a high practical and research value in the field of freight volume forecasting.
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2017年第1期180-183,共4页
Journal of Railway Science and Engineering
基金
长江学者和创新团队发展计划资助项目(IRT15R29)
