| 基于因子分析和曲线拟合的集装箱吞吐量预测 |
| |
| 引用本文： | 贾飞跃,韩晓龙.基于因子分析和曲线拟合的集装箱吞吐量预测[J].上海海事大学学报,2019,40(2):18-22. |
| |
| 作者姓名： | 贾飞跃 韩晓龙 |
| |
| 作者单位： | 上海海事大学物流科学与工程研究院 |
| |
| 基金项目： | 国家自然科学基金（71471110）；上海市科学技术委员会创新项目（16DZ1201402,16040501500）；上海市科学技术委员会工程中心能力提升项目（14DZ2280200）；上海海事大学研究生学术新人培育计划（YXR2017014） |
| |
| 摘 要： | 为提高集装箱吞吐量的预测精度,提出基于因子分析和曲线拟合的集装箱吞吐量预测模型。以上海港为例,通过因子分析,分析影响集装箱吞吐量的主要因素,筛选出主因子,得到不同年份的综合经济发展值;再运用曲线拟合方法,建立以综合经济发展值为自变量,以集装箱吞吐量为因变量的三次曲线模型;运用自回归积分移动平均(autoregressive integrated moving average,ARIMA)模型预测2016—2020年的综合经济发展值,进而求得2016—2020年上海港集装箱吞吐量预测值。结果表明:该模型的拟合效果和预测精度均较高,可以运用到集装箱吞吐量预测中。给出上海港在国内经济新常态下转型升级的建议。
|
| 关 键 词： | 自回归积分移动平均（autoregressive integrated moving average ARIMA）模型 因子分析 曲线拟合 集装箱吞吐量预测 |
| 收稿时间： | 2018/6/2 0:00:00 |
| 修稿时间： | 2018/8/11 0:00:00 |
Prediction of container throughput based on factor analysis and curve fitting |
| |
| Institution: | Logistics Research Center,Shanghai Maritime University |
| |
| Abstract: | In order to improve the prediction accuracy of container throughput, a container throughput prodiction model based on factor analysis and curve fitting is proposed. Shanghai Port is taken as an example. Through factor analysis, the main factors affecting the container throughput are analyzed, the principal component factors are selected, and the comprehensive economic development values of different years are obtained; a curve fitting method is used to establish a cubic curve model, where the comprehensive economic development value is taken as an independent variable and the container throughput is taken as a dependent variable; the comprehensive economic development values of 2016 2020 are predicted by the autoregressive integrated moving average (ARIMA) model, thus the predicted values of the container throughput of Shanghai Port in 2016 2020 are obtained. The results show that the fitting effect and the prediction accuracy of the model are both high and can be applied to the container throughput prediction. The suggestions of the transformation and upgrading of Shanghai Port under the new normal of Chinese economy are given. |
| |
| Keywords: | autoregressive integrated moving average (ARIMA) model factor analysis curve fitting container throughput prediction |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《上海海事大学学报》浏览原始摘要信息 |
| 点击此处可从《上海海事大学学报》下载免费的PDF全文 |
|
