Predictions on Seaports Freight Throughput based on the Extreme Learning Machine Neural Network

DOI

10.2991/icmemtc-16.2016.341How to use a DOI?

Keywords

Extreme Learning Machine; Neural Networks; Support Vector Machine; Seaports Freight Throughput; Prediction Model

Abstract

The researches and predictions on seaports freight throughput in China have become increasingly important as the fast growth of Chinese economy and the development of "the Silk Road Economic Belt and the 21st-Century Maritime Silk Road". Extreme Learning Machine, a relatively new neural network algorithm published in the last a few years, is creatively utilized in this paper to mine historical data of seaports freight throughput in China. A new prediction model is built to predict seaports freight throughput in China. According to test results, the model shows good performances. The researches presented in this paper may be valuable for both real applications and theoretical studies.

Copyright

© 2016, 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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TY  - CONF
AU  - Nan Yao
PY  - 2016/04
DA  - 2016/04
TI  - Predictions on Seaports Freight Throughput based on the Extreme Learning Machine Neural Network
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1811
EP  - 1814
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.341
DO  - 10.2991/icmemtc-16.2016.341
ID  - Yao2016/04
ER  -