物流园区物流需求的灰色预测研究——以重庆空港物流园为例  

Application of Gray Model in Logistics Demand for Chongqing Airport Logistics Park

作　　者：吴涵[1] 

机构地区：[1]重庆工商大学融智学院,重庆400065

出　　处：《物流科技》2016年第9期13-16,共4页Logistics Sci-Tech

摘　　要：物流需求预测是物流园区整体规划的重要前提,准确的物流需求预测可以大大提高物流园区规划的科学性。灰色GM(1,1)模型利用累加生成后的新数据建模,容易找出数据变换规律,计算简便,具有所需样本数据少且预测效果较好的优点。文章以重庆空港物流园为例,选取基于方根变换的灰色GM(1,1)改进模型对重庆空港物流园的物流需求量进行预测,得出了2020年的预测值。研究表明,灰色预测模型具有对数据要求限制少、中短期预测精准等优点,适合对物流需求进行预测,该方法在物流园区物流需求预测中具有推广应用价值。Logistics demand prediction is an important prerequisite for the overall plan of a logistics park in that the plan can be dramatically improved in the nature of science by a precious forecast. GM（1,1）model is established on the new data from accumulations, which can easily find the rule of data changing and simplify the computations. Besides, merely small sample data are required while the prediction is effective. This paper take an example of the Chongqing airport logistics park, based on the root transformation, this article applies an improved grey GM（1,1）model to the logistics demand forecasting of Chongqing airport logistics park, extracting the prediction volumes of 2020. This research indicates that a grey forecasting model imposes less limitation on data and then produce a precious forecasting, which seems to be applicable to predict the logistics demand. In this case,the model deserves to extended application in the logistics park.

关 键 词：需求预测 灰色系统 GM(1 1)模型 方根变换 

分 类 号：F719[经济管理—产业经济]