한국해양대학교

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Application of Machine and Deep Learning to Mooring, Dynamic Positioning, and Ship Berthing Systems

Title
Application of Machine and Deep Learning to Mooring, Dynamic Positioning, and Ship Berthing Systems
Author(s)
이대수
Keyword
Machine learningDeep learningMooring systemDynamic positioning system (DPS)Automatic berthing system
Issued Date
2020
Publisher
한국해양대학교 대학원
URI
http://repository.kmou.ac.kr/handle/2014.oak/12474
http://kmou.dcollection.net/common/orgView/200000342184
Abstract
In recent years, there have been a surge of advances in machine and deep learning due to accessibility to a large amount of digital data, developments in computer hardware, and state-of-the-art machine and deep learning algorithms proposed. The robust performance of the recent machine and deep learning algorithms have been proven in many applications such as natural language processing, computer vision, market research, self-driving car, autonomous shipping, and so on. The application of machine and deep learning is very powerful in a sense that one does not need to build such a complex and hard-coded system to implement sophisticated functionality. Instead, a machine and deep learning-based system can be trained on a collected training dataset and the trained system can robustly perform as desired. There are two main advantages of the use of machine and deep learning-based systems over the traditional hard-coded systems. First, as mentioned, the machine and deep learning-based systems do not require such complex and hard-coded algorithms, therefore, such learning systems are less prone to errors and faster to implement without much debugging. Second, the machine and deep learning-based systems can adapt to varying circumstances through re-training based on collected data. An example of the varying circumstance can be a varying purchase trend impacted by the media. Therefore, even if the input distribution from the circumstance changes over time, the machine and deep learning-based systems can easily adapt. In this paper, the machine and deep learning algorithms are applied to various applications such as a mooring system, dynamic positioning system (DPS), and ship berthing system. Specifically, the machine and deep learning algorithms are utilized to build a mooring line tension prediction system, a feed-forward system for DPS, an adaptive proportional-integral-derivative (PID) controller for DPS, and an automatic ship berthing system.
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조선해양시스템공학과 > Thesis
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