Ανάπτυξη μεθοδολογίας για την αναγνώριση επικίνδυνων καταστάσεων πλοίων μέσω τεχνητού ανοσοποιητικού συστήματος, λαμβάνοντας υπόψη παράγοντες ρίσκου για ατυχήματα προσάραξης

Kalogridakis, Georgios; Καλογριδάκης, Γεώργιος

dc.contributor.author	Kalogridakis, Georgios	en
dc.contributor.author	Καλογριδάκης, Γεώργιος	el
dc.date.accessioned	2025-01-13T11:50:35Z
dc.date.available	2025-01-13T11:50:35Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/60713
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.28409
dc.rights	Αναφορά Δημιουργού 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/gr/	*
dc.subject	Risk analysis	en
dc.subject	Artificial Immune Systems	en
dc.subject	Risk factors	en
dc.subject	Grounding	en
dc.subject	Negative selection algorithm	en
dc.subject	Ανάλυση ρίσκου	el
dc.subject	Τεχνητό ανοσοποιητικό σύστημα	el
dc.subject	Παράγοντες ρίσκου	el
dc.subject	Προσάραξη πλοίων	el
dc.subject	Αναγνώριση κινδύνων πλοίου	el
dc.title	Ανάπτυξη μεθοδολογίας για την αναγνώριση επικίνδυνων καταστάσεων πλοίων μέσω τεχνητού ανοσοποιητικού συστήματος, λαμβάνοντας υπόψη παράγοντες ρίσκου για ατυχήματα προσάραξης	el
heal.type	bachelorThesis
heal.classification	Risk analysis	en
heal.classification	Artificial Immune Systems	en
heal.language	el
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2024-07-18
heal.abstract	In this diploma thesis, a method for analyzing and assessing the risk of situations that could lead to grounding accidents was developed, by analyzing risk factors and using a method inspired by a function of the human immune system. The main advantages of the method that make its application interesting are that only data from safe situations are required to identify dangerous ones and that the process of probability calculations is avoided. Initially, an analysis of the risk factors that may contribute to grounding accidents is presented, while they are also categorized according to their impact. Then, a brief explanation of the functioning of the human immune system follows, and later the chosen method is mentioned and explained, referring to its origin, characteristics, and some application examples. Specifically, the method is inspired by the Negative Selection mechanism, which is essentially related to the human body's ability to distinguish its own cells from foreign invaders. The application is based on the parallelism of the ship's safe situations with human cells and the dangerous situations with foreign invaders. The algorithm used falls under the category of Negative Selection Algorithms. The process initially involves the introduction of safe situations (self) and then the construction of detectors that identify the dangerous ones. The safe situations were constructed with appropriate criteria, while the method was applied separately for each category of risk factors. Subsequently, information was assigned to the detectors regarding the situations they identify. Finally, an application in four real operational situations is carried out. Conclusively, the method seems to have satisfactory results in terms of detecting a dangerous situation and providing information about it, but at the same time, it is observed that the method presents various difficulties in its application which require special attention.	en
heal.advisorName	Ventikos, Nikolaos	en
heal.advisorName	Louzis, Konstantinos	en
heal.committeeMemberName	Themelis, Nikolaos	en
heal.committeeMemberName	Eliopoulou, Eleftheria	en
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ναυπηγών Μηχανολόγων Μηχανικών. Τομέας Μελέτης Πλοίου και Θαλάσσιων Μεταφορών	el
heal.academicPublisherID	ntua
heal.numberOfPages	98 σ.	el
heal.fullTextAvailability	false