Machine learning in the maritime environment

A study in the International Journal of Shipping and Transport Logistics addresses a longstanding gap in the world of dry bulk shipping terminals, introducing a two-stage methodology that employs unsupervised machine learning techniques. The work by Iñigo L. Ansorena of the Universidad Internacional de La Rioja in Spain, focused on North European dry bulk terminals, and could improve transparency in terminal management.

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