Bachelor and Master Theses

Title: Ocean Waves Estimation
Subject: Computer Science
Level: Advanced
Description: This thesis aims to solve the mathematical inverse problem of characterizing sea waves based
on the responses obtained from a marine vessel sailing under certain sea conditions. By researching
this problem the thesis contributes to the marine industry by improving products that are using
ocean behavior for controlling ship's dynamics.
Knowledge about the current state of the sea, such as the wave frequency and height, is important
for navigation, control, and for the safety of a vessel. This information can be retrieved from
specialized weather reports. However, such information is not at all time possible to obtain during
a voyage, and if so usually comes with a certain delay. Therefore this thesis seeks solutions that can
estimate on-line the waves' state using methods in the field of Artificial Intelligence. The specific
investigation methods are Transfer Functions augmented with Genetic Algorithm, Artificial Neural
Networks and Case-Based Reasoning. These methods have been configured and validated using the
n-fold cross validation method. All the methods have been tested with an actual implementation.
The algorithms have been trained with data acquired from a marine simulation program developed
in Simulink. The methods have also been trained and tested using monitored data acquired from
an actual ship sailing on the Baltic Sea as well as wave data obtained from a buoy located nearby
the vessel's route. The proposed methods have been compared with state-of-the art reports in
order evaluate the novelty of the research and its potential applications in industry.
The results in this thesis show that the proposed methods can in fact be used for solving the
inverse problem. It was also found that among the investigated methods it is the Transfer Function
augmented with Genetic Algorithm which yields best results.
This Master Thesis is conducted under the Master of Engineering Program in Robotics at
Mälardalens högskola in Västerås, Sweden. The thesis was proposed by Q-TAGG R&D AB in
Västerås, Sweden, a company which specializes in marine vessel dynamics research.
Company: Q-TAGG R&D AB, kontaktperson: George Fodor
Prel. end date: 2017-05-17
Presentation date: 2017-06-01
Student: Andreas Ramberg
IDT supervisor: Giacomo Spampinato, 46-21-101304
Examinator: Ning Xiong
Ning Xiong, +46-21-151716

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2017-05-17, 22:42

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