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| 逻辑斯蒂增长模型在集装箱运量长期预测中的应用 | |
| 引用本文： | 杨波,余建星,王谦.逻辑斯蒂增长模型在集装箱运量长期预测中的应用[J].海洋技术,2006,25(4):88-93. |
| 作者姓名： | 杨波 余建星 王谦 |
| 作者单位： | 1. 天津大学建筑工程学院,天津,300192;伟信(天津)工程咨询有限公司,天津,300050 2. 天津大学建筑工程学院,天津,300192 3. 伟信(天津)工程咨询有限公司,天津,300050 |
| 摘 要： | 多因素动态生成系数法是目前集装箱吞吐量预测方法中最为成熟、应用最为广泛的预测方法。该办法首先确定外贸年增长率预测外贸量,然后通过生成系数得到集装箱吞吐量预测值。然而,在进行中长期集装箱吞吐量预测时,未来外贸年增长率的确定经常缺乏依据,导致长期预测结果精度较差。论文通过利用逻辑斯蒂增长模型进行中长期经济增长预测,再利用经济增长与外贸量的回归分析进行外贸量预测来解决这一问题,最终完成了天津港2005~2020年集装箱吞吐量预测的任务。从原理和结果上看,逻辑斯蒂增长模型是更为适宜和先进的方法,可以用来改进多因素动态生成系数法,提高中长期集装箱预测的精度。 |
| 关 键 词： | 多因素动态生成系数法 逻辑斯蒂模型 AR(1)预测 中长期预测 |
| 文章编号： | 1003-2029（2006）04-0088-06 |
| 收稿时间： | 2006-06-22 |
| 修稿时间： | 2006年6月22日 |
The Application of the Logistics Model in the Middle/Long Term Container Prediction |
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| YANG Bo,YU Jian-xing,WANG Qian.The Application of the Logistics Model in the Middle/Long Term Container Prediction[J].Ocean Technology,2006,25(4):88-93. | |
| Authors: | YANG Bo YU Jian-xing WANG Qian |
| Institution: | 1. College of Civil engineering, Tianjin University, Tianjin 300192, China ; 2. Scottwilson (Tianjin |
| Abstract: | Multi-factor dynamic product coefficients method is the most mature and widely-used one in all available container handling capacity prediction models.After predicting foreign trade value,predicted container handling capacity can be got by using product coefficients.However,the very first step,setting future foreign exchanging growth rate,is a step which usually lacks solid logical base,leading to low precision in the middle/long term prediction.This paper adopts logistic model to make middle/long term GDP,then solves this logic-lacking problem by using regression model between economic volume and foreign trade value.The middle/long term container handling capacity for the Tianjin Port is conducted as a case.The result and rationales show that logistic model is a more appropriate and advanced method to modify the multi-factor dynamic product coefficients and improve middle/long term prediction's precision. |
| Keywords: | multi-factor dynamic product coefficients method AR(1) prediction middle/long term prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |