Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/151132
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zhou, Qingji | en_US |
dc.contributor.author | Wong, Yiik Diew | en_US |
dc.contributor.author | Loh, Hui Shan | en_US |
dc.contributor.author | Yuen, Kum Fai | en_US |
dc.date.accessioned | 2021-06-24T10:13:51Z | - |
dc.date.available | 2021-06-24T10:13:51Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Zhou, 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/10.1080/03088839.2019.1569765 | en_US |
dc.identifier.issn | 0308-8839 | en_US |
dc.identifier.other | 0000-0002-5832-1304 | - |
dc.identifier.other | 0000-0001-7419-5777 | - |
dc.identifier.other | 0000-0002-9199-6661 | - |
dc.identifier.uri | https://hdl.handle.net/10356/151132 | - |
dc.description.abstract | Adaptive 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.sponsorship | Singapore Maritime Institute (SMI) | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Maritime Policy and Management | en_US |
dc.rights | © 2019 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. | en_US |
dc.subject | Engineering::Environmental engineering | en_US |
dc.title | ANFIS model for assessing near-miss risk during tanker shipping voyages | en_US |
dc.type | Journal Article | en |
dc.contributor.school | School of Civil and Environmental Engineering | en_US |
dc.contributor.research | Maritime Institute | en_US |
dc.identifier.doi | 10.1080/03088839.2019.1569765 | - |
dc.identifier.scopus | 2-s2.0-85060637053 | - |
dc.identifier.issue | 4 | en_US |
dc.identifier.volume | 46 | en_US |
dc.identifier.spage | 377 | en_US |
dc.identifier.epage | 393 | en_US |
dc.subject.keywords | Near-miss Incident | en_US |
dc.subject.keywords | Tanker Shipping | en_US |
dc.description.acknowledgement | This work was supported by Singapore Maritime Institute to which the authors express their gratitude. | en_US |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
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
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.