Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151132
Full metadata record
DC FieldValueLanguage
dc.contributor.authorZhou, Qingjien_US
dc.contributor.authorWong, Yiik Diewen_US
dc.contributor.authorLoh, Hui Shanen_US
dc.contributor.authorYuen, Kum Faien_US
dc.date.accessioned2021-06-24T10:13:51Z-
dc.date.available2021-06-24T10:13:51Z-
dc.date.issued2019-
dc.identifier.citationZhou, Q., Wong, Y. D., Loh, H. S. & Yuen, K. F. (2019). ANFIS model for assessing near-miss risk during tanker shipping voyages. Maritime Policy and Management, 46(4), 377-393. https://dx.doi.org/10.1080/03088839.2019.1569765en_US
dc.identifier.issn0308-8839en_US
dc.identifier.other0000-0002-5832-1304-
dc.identifier.other0000-0001-7419-5777-
dc.identifier.other0000-0002-9199-6661-
dc.identifier.urihttps://hdl.handle.net/10356/151132-
dc.description.abstractAdaptive neuro-fuzzy inference system (ANFIS) was applied to predict the risk of near-miss incidents during tanker shipping voyages. Firstly, near-miss incidents recorded by a global tanker shipping management company were analysed. Four variables—type of operation, vessel’s location, on-board position, and harm potential were selected to train and predict the risk levels of near-miss incidents. The selected variables were found to be correlated with the observed frequency at three risk levels, namely low, medium and high. Gravity factor (GF) was calculated using the frequency of the categories in each variable and their associated risk levels. The calculated GF values and the risk levels of near-miss incidents were used as input values in the ANFIS model. Triangular, Trapezoidal and Gaussian membership functions were used. Subsequently, fuzzy logical theory and artificial neural networks were applied to train the data. Causal factors in terms of direct contributory factors, indirect contributory factors and root contributory factors to the near-miss incidents were analysed. Risk control measures were also proposed to improve safety during tanker shipping.en_US
dc.description.sponsorshipSingapore Maritime Institute (SMI)en_US
dc.language.isoenen_US
dc.relation.ispartofMaritime Policy and Managementen_US
dc.rights© 2019 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.en_US
dc.subjectEngineering::Environmental engineeringen_US
dc.titleANFIS model for assessing near-miss risk during tanker shipping voyagesen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.contributor.researchMaritime Instituteen_US
dc.identifier.doi10.1080/03088839.2019.1569765-
dc.identifier.scopus2-s2.0-85060637053-
dc.identifier.issue4en_US
dc.identifier.volume46en_US
dc.identifier.spage377en_US
dc.identifier.epage393en_US
dc.subject.keywordsNear-miss Incidenten_US
dc.subject.keywordsTanker Shippingen_US
dc.description.acknowledgementThis work was supported by Singapore Maritime Institute to which the authors express their gratitude.en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:CEE Journal Articles

SCOPUSTM   
Citations 20

16
Updated on Mar 25, 2024

Web of ScienceTM
Citations 20

14
Updated on Oct 30, 2023

Page view(s)

246
Updated on Mar 28, 2024

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.