| 基于灰色GM(1，n)模型的河北物流货运量预测 |
| Forecast of Logistics Freight Volume in Hebei Province Based [STHZ]on Grey GM (1, n) Model |
| 投稿时间：2014-12-25 |
| 中文关键词:货运量 预测 灰色关联分析 GM(1，n)模型 河北省 |
| 英文关键词:freight volume forecast grey relational analysis GM (1, n) model Hebei province |
| 基金项目:河北省教育厅重点项目（SD141049），河北省社科基金项目（HB14GL022），河北省教育厅人文社科重点基地。 |
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| 中文摘要: |
| 在分析河北省货运量影响因素的基础上，提出了基于灰色关联分析的灰色GM(1,n)预测模型。在国家统计局指标分类基础上，将河北省货运量影响因素分为国民经济、固定资产投资和房地产、对外经济贸易、能源、运输和邮电、社会消费六类18个指标，采用灰色关联分析法对18项指标与河北省货运量进行相关性分析，根据灰色关联系数与排序，筛选灰色GM(1,n)预测变量，减少预测模型输入工作量，计算模型参数。通过对河北省1993—2012年货运量实例分析表明，该预测方法具有运算快、精度高的优点。 |
| 英文摘要: |
| The prediction model is proposed to improve forecast level of the logistics demand in Hebei Province. The grey prediction GM (1, n) model based on grey relational analysis is constructed by analyzing the influencing factors on traffic volume in Hebei province. Firstly, according to the classification of the national bureau of statistics indexes, influencing factors on freight volume in Hebei province are divided into 6 categories (18 indexes) : the national economy, investment in fixed assets and real estate, foreign economic and trade, energy, transportation and post and telecommunications and social spending. Secondly, a correlation analysis is made on 18 indexed and freight volume in Hebei province using grey relational analysis method. Next, According to grey relation coefficient and sorting theory, the grey GM (1, n) prediction variables is screened to reduce the input work load of the forecasting model so as to calculate the model parameters efficiently. Finally, the freight volume data (1993—2012) in Hebei province are input into the model to make an example analysis, and it is shown that the forecasting method has some advantages such as fast operation, high accuracy and so on. |
| 赵莉琴,刘敬严.基于灰色GM(1，n)模型的河北物流货运量预测[J].石家庄铁道大学学报(社会科学版),2015(2):10-15. |
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