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Two AI Case Studies in Danish Maritime Shipping
Beskrivelse
The Danish maritime shipping industry is in the middle of a major digital transformation. In this talk, we present two case studies of AI techniques that play central roles in this development.
The first is a stowage optimization method for containerships that enable liner shipping companies like Maersk to stow more cargo on their vessels and steer sales toward profitable bookings. The second is a machine learning technique for predicting the destination of tanker vessels from AIS positioning data. It is used by TORM to forecast market development and move their fleet to locations with expected demand.
Talere
Nikolaj Bläser - Data scientist & Industrial PhD Fellow - TORM
Búgvi Benjamin Magnussen - Data scientist & Industrial PhD Fellow - TORM
Rune Møller Jensen - Associate Professor - IT University of Copenhagen
Búgvi Benjamin Magnussen - Data scientist & Industrial PhD Fellow - TORM
Rune Møller Jensen - Associate Professor - IT University of Copenhagen
Dato & Tid
torsdag den 9. november 2023, 11.15 - 11.45
Sal
Sal 2
Temaer
Robotics og Fremtidens Teknologier, Maritim