Predicting Shipping Freight Rate Movements Using Recurrent Neural Networks and AIS Data
Predicting Shipping Freight Rate Movements Using Recurrent Neural Networks and AIS Data On the tanker route between the Arabian Gulf and Singapore Stian Røyset Salen Gisle Hoel Århus Industrial Economics and Technology Management Submission date: June 2018 Supervisor: Sjur Westgaard, IØT Norwegian University of Science and Technology Department of Industrial Economics and Technology Management Preface This master's thesis represents the finalisation of our second Master of Science (MSc) degrees at the Norwegian University of Science and Technology (NTNU), after completing our MSc degrees in Marine Technology at NTNU in 2016. The current thesis is part of the specialisation program Financial Engineering in the study program Industrial Economics and Technology Management, and it was written in the spring of 2018. There are several people to whom we would like to express our sincere gratitude, for making this thesis possible. Firstly, we would like to thank our supervisor, Professor Sjur Westgaard at the Department of Industrial Economics and Technology Management at NTNU. Further, we want to thank Professor Keith Downing, at the Department of Computer and Information Science at NTNU, for kindly helping us with machine learning related issues. Moreover, the Norwegian Coastal Administration, Professor Bjørn Egil Asbjørnslett at the Department of Marine Technology at NTNU, and particularly PhD in Marine Technology, Carl Fredrik Rehn, and MSc in Marine Technology, Bjørnar Brende Smestad, deserve a thanks for providing AIS data, inspiration, useful discussions and help along the way. Lastly, we give thanks to our friends who have supported us, proofread the thesis and provided useful advices. Trondheim, June 11, 2018 Gisle Hoel Arhus˚ and Stian Røyset Salen ii Abstract The purpose of this thesis is twofold.
[Show full text]