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2022 Journal Impact Factor - 0.6
2022 CiteScore - 1.7




ISSN 2083-6473
ISSN 2083-6481 (electronic version)




Associate Editor
Prof. Tomasz Neumann

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
Estimation of Shipment Size in Seaborne Iron Ore Trade
1 Shanghai Maritime University, Shanghai, China
Times cited (SCOPUS): 3
ABSTRACT: Shipment size is unavailable and important in AIS-based trade volume estimates. A method of shipment size estimates based on AIS (Automatic Identification System) data and BP neural network is proposed. The ship's length, width, designed draught, current draught and deadweight ton are input parameters, the actual shipment size of the ship is output value, and the BP neural network is trained to estimate the actual shipment size of the iron ore carriers. Then, the AIS data is used to calculate the iron ore trade volume in 2018. Compared with customs data, the annual error of import volume of China is less than 0.5%. The result shows that the proposed method is accurate and practical.
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Citation note:
Zhou X., Hu Q.: Estimation of Shipment Size in Seaborne Iron Ore Trade. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 13, No. 4, doi:10.12716/1001.13.04.11, pp. 791-796, 2019

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