Novel assessment and prediction method for vessel traffic risk degree
Bo Li
Journal of Risk and Reliability, 2022, vol. 236, issue 5, 781-796
Abstract:
To assess the current risk degree and predict the future risk degree of vessel traffic, a novel method is put forward in this study. Different from the existing literature, the available evidence of vessel traffic is directly transformed into the weighted basic probabilistic assignment (BPA) based on the optimal solution to the intersection of fuzzy membership functions in the framework of D-S evidence theory. The matrix deformation algorithm towards the combination rule makes the time complexity low in the process of the risk degree assessment. With respect to the risk degree prediction, the required Sigma points are effectively extracted. We derive the adaptive filtering gain that is suitable for the rapidly changing BPA. Finally, the experiments of vessel traffic in the Dalin Bay are made to indicate performance of the proposed method.
Keywords: Risk degree; evidence combination; unscented transform; complexity; matrix deformation (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X211039405 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:236:y:2022:i:5:p:781-796
DOI: 10.1177/1748006X211039405
Access Statistics for this article
More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().