中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2020, Vol. 39 ›› Issue (04): 36-40.DOI: 10.3969/j.issn.1674-0696.2020.04.07

• 交通运输工程 • 上一篇    下一篇

基于自适应滤波改进算法的大连港吞吐量预测

李颖,付金宇,张照亿,高朋举   

  1. (大连海事大学 航海学院 环境信息研究所,辽宁 大连 116026)
  • 收稿日期:2018-07-01 修回日期:2019-02-11 出版日期:2020-04-21 发布日期:2020-04-21
  • 作者简介:李颖(1968— ),女,辽字锦州人,教授,博士,主要从事海洋环境污染遥感检测等研究工作。E-mail:yldmu@126.com。 通信作者:付金宇(1994—),男,黑龙江牡丹江人,硕士研究生,主要从事船舶尾气扩散及相关控制系统设计等研究。E-mail:18642861102@sina.cn。
  • 基金资助:
    国家重点研发专项(2017YFC0211904);中央高校基本科研业务费专项资助(3132014302)

Dalian Port Throughput Prediction Based on Improved Adaptive Filtering Algorithm

LI Ying,FU Jinyu, ZHANG Zhaoyi, GAO Pengju   

  1. (Research Institute of Environmental Information, College of Navigation, Dalian Maritime University, Dalian 116026, Liaoning, China)
  • Received:2018-07-01 Revised:2019-02-11 Online:2020-04-21 Published:2020-04-21

摘要: 为了有效对大连港港口吞吐量进行预测,引入自适应滤波算法,利用MATLAB仿真模型构建未来港口吞吐量预测模型,其中包括实验模拟过程,技术原理及理论模型。预测结果由改进的自适应滤波算法得到,结合设置的不同的增幅等级,进行不同程度的校正。结果表明,通过模型设定的小误差,选择4个权重,通过迭代运算得到最佳权重,然后应用于下一组数据进行预测。研究表明:使用改进后的自适应滤波算法港口吞吐量预测值的方差和标准差分别从改进前的0.019 899、0.141 064提升到改进后的0.008 172、0.090 399,说明该模型能够有效预测随后几年的港口吞吐量。

关键词: 交通运输工程, 自适应滤波, 预测模型, 迭代运算, 港口吞吐量, 校正

Abstract: In order to effectively forecast the throughput of Dalian port, an adaptive filtering algorithm was introduced. By use of MATLAB simulation model, a future port throughput prediction model was established, which included the experimental simulation process, technical principles and theoretical models. The prediction results were obtained by an improved adaptive filtering algorithm. Combined with setting different amplification levels, different degrees of correction were performed. The results indicate that: through the small error set by the model, four weights are selected and the best weight is obtained by iterative operation, and then it is applied to the next group of data for prediction. The research shows that the variance and standard deviation of the prediction value of port throughput obtained by the improved adaptive filtering algorithm are respectively improved from 0.019 899 and 0.141 064 before improvement to 0.008 172 and 0.090 399 after improvement, which indicates that the proposed model can effectively predict the port throughput in the following years.

Key words: traffic and transportation engineering, adaptive filtering, prediction model, iterative operation, port throughput, correction

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