Forecasting container throughput with big data using a partially combined framework-Reference-Cited by-同舟云学术

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Forecasting container throughput with big data using a partially combined framework

Published:2015-06 Issue: Volume: Page:
ISSN:
Container-title:2015 International Conference on Transportation Information and Safety (ICTIS)
language:
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Author:

Huang Anqiang,Zhang Zhenji,Shi Xianliang,Hua Guowei

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7210493/7232046/07232102.pdf?arnumber=7232102

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nonparametric Functional Data Analysis for Forecasting Container Throughput: The Case of Shanghai Port;Journal of Marine Science and Engineering;2022-11-10

2. The Analysis of Container Terminal Throughput Using ARIMA and SARIMA;Advanced Structured Materials;2022

3. A model for port throughput forecasting using Bayesian estimation;Maritime Economics & Logistics;2021-03-17

4. A Prediction Model of the Sum of Container Based on Combined BP Neural Network and SVM;J INF PROCESS SYST;2019

5. The impact of seasonal demand fluctuations on service network design of container feeder lines;Journal of Transportation and Logistics;2016-04-30

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