Proceedings of the 2018 International Symposium on Social Science and Management Innovation (SSMI 2018)

Forecasting Port Throughput Model of Tianjin Port based on Wavelet Analysis and Machine Learning

Authors
Bingchun Liu, Shaofeng Feng
Corresponding Author
Shaofeng Feng
Available Online February 2019.
DOI
10.2991/ssmi-18.2019.50How to use a DOI?
Keywords
Tianjin port, cargo throughput, machine learning, forecasting, wavelet analysis.
Abstract

With the development of national economy, the importance of port growing port is the national foreign trade portal, is the driving force for the development of the city, with the improvement of freight volume, how many directly affects the port cargo throughput of port layout planning, therefore, to effectively predict the Tianjin port cargo throughput is very important to the correct port development policy. This article embarks from the analysis of Tianjin port cargo throughput changes year by year, from 2001 to 2017, Tianjin port cargo throughput are summarized factors index, prediction model was established based on seven kinds of machine learning algorithms and wavelet analysis, in Tianjin, for example, through the training data model, and then the model prediction data were compared with the actual data analysis, weighing error, select the optimal model, it is concluded that the prediction data and the actual data, the basic of Tianjin port cargo throughput forecast has positive significance.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Symposium on Social Science and Management Innovation (SSMI 2018)
Series
Advances in Economics, Business and Management Research
Publication Date
February 2019
ISBN
978-94-6252-667-9
ISSN
2352-5428
DOI
10.2991/ssmi-18.2019.50How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Bingchun Liu
AU  - Shaofeng Feng
PY  - 2019/02
DA  - 2019/02
TI  - Forecasting Port Throughput Model of Tianjin Port based on Wavelet Analysis and Machine Learning
BT  - Proceedings of the 2018 International Symposium on Social Science and Management Innovation (SSMI 2018)
PB  - Atlantis Press
SP  - 282
EP  - 285
SN  - 2352-5428
UR  - https://doi.org/10.2991/ssmi-18.2019.50
DO  - 10.2991/ssmi-18.2019.50
ID  - Liu2019/02
ER  -