- Tytuł:
- Estimation of Shipment Size in Seaborne Iron Ore Trade
- Autorzy:
-
Zhou, X.
Hu, Q. - Powiązania:
- https://bibliotekanauki.pl/articles/117393.pdf
- Data publikacji:
- 2019
- Wydawca:
- Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
- Tematy:
-
cargo handling
shipment size
estimation of shipment size
seaborne iron ore trade
AIS Data
Maritime Mobile Service Identify (MMSI)
BP Neural Network
iron ore - Opis:
- 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.
- Źródło:
-
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2019, 13, 4; 791-796
2083-6473
2083-6481 - Pojawia się w:
- TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
- Dostawca treści:
- Biblioteka Nauki
Artykuł