A Fuzzy Rule-Based Ship Risk Profile Prediction Model for Port State Control Inspections

S. M.Esad Demirci*, Kadir Cicek, Ulku Ozturk

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

Maritime transport is the backbone of the international trade, more than 80% of global freight transport is carried by ships on the seas. However, in a complex and high-risk environment at sea, substandard ships in maritime transport causes serious accidents and hence bring out many threats to the maritime industry. As a result, with the aim of detection and elimination the substandard ships, port state controls (PSC) have been developed to inspect the ships respect to their Ship Risk Profile (SRP). SRP helps to determine the ship’s priority for PSC inspections through categorizing the ships in high risk, standard risk or low risk using various generic and historic parameters. In this study a new model is proposed to predict SRP by using fuzzy clustering analysis (FCA) and fuzzy rule-based classification system (FRBS) different from the standard calculation of the SRP in the PSC regimes. The proposed model is structured on five different parameters which are ship type, ship flag, ship age, deficiency number and detention. In the proposed model, to predict the SRP, 53788 ship inspection data belonging to the parameters has been analyzed gathered from the Paris MoU online database between the years of 2017 and 2020. The results obtained with the proposed approach help to identify the risk profile for the ship targeted at almost certain risk level. As a result of the study, it is aimed to provide decision supports for port state control (PSC) officers to detect the most appropriate/risky ship for the inspection.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
EditörlerCengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar498-505
Sayfa sayısı8
ISBN (Basılı)9783030855765
DOI'lar
Yayın durumuYayınlandı - 2022
EtkinlikInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Turkey
Süre: 24 Ağu 202126 Ağu 2021

Yayın serisi

AdıLecture Notes in Networks and Systems
Hacim308
ISSN (Basılı)2367-3370
ISSN (Elektronik)2367-3389

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???event.eventtypes.event.conference???International Conference on Intelligent and Fuzzy Systems, INFUS 2021
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot24/08/2126/08/21

Bibliyografik not

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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