This publication deals with the evaluation of forecasting the emissions of ships operating in the port through neural networks. Analyzed particulate matter (PM1, PM2.5, PM10, TSP) emissions from ships at various parts of the port. The research is based on usage of AIS system data, the technical database of the ship, the ambient air measurement data and the ambient air pollution measuring data for the use of neural network training. Results showed that trained neuronal networks could be sufficiently accurate (the correlation coefficient amounted from 0.82 to 0.92 depending on pollutant) to use for ship operating in the port emissions evaluation.
Artificial Neural Network Model Use for Particulate Matter Evaluation from Ships in Klaipeda Port
Lecture Notes in Intelligent Transportation and Infrastructure
International Conference TRANSBALTICA: Transportation Science and Technology ; 2022 ; Vilnius, Lithuania September 15, 2022 - September 16, 2022
2023-02-22
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Air Pollution by NO~x from Ships Passing Klaipeda Port Channel
British Library Conference Proceedings | 2012
|Ships Squat Study Impact on Under Keel Clearance in Port of Klaipėda
British Library Conference Proceedings | 2014
|Klaipeda port entrance rehabilitation project
British Library Conference Proceedings | 2002
|Port Entrance Channel Optimization in Klaipeda Port
British Library Conference Proceedings | 2012
|