Vessel and Port Efficiency Metrics through Validated AIS data

  title={Vessel and Port Efficiency Metrics through Validated AIS data},
  author={Tomaz Martincic and Dejan {\vS}tepec and Jo{\~a}o Pita Costa and Kristijan {\vC}agran and Athanasios Chaldeakis},
  journal={Global Oceans 2020: Singapore – U.S. Gulf Coast},
Automatic Identification System (AIS) data represents a rich source of information about maritime traffic and offers a great potential for data analytics and predictive modelling solutions, which can help optimizing logistic chains and reducing environmental impacts. In this work, we address the main limitations of the validity of AIS navigational data fields, by proposing a machine learning-based data-driven methodology to detect and (to the possible extent) also correct erroneous data… Expand

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