Application of Dempster–Shafer theory for the quantification and propagation of the uncertainty caused by the use of AIS data

Talavera, Alejandro; Aguasca, Ricardo; Galván, Blas; Cacereño, Andrés

doi:10.1016/j.ress.2012.10.007

Cited by 44 publications

(20 citation statements)

References 16 publications

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“…Determine the collision risk of maritime traffic in a sea area[103] Risk can be defined as the probability of occurrence of an unwanted event multiplied by the consequences of that same event. (p. Examine the feasibility of data-based generalized linear modeling technique to risk analysis of navigation[104] Not defined2013 N/A R $ (P x , A) I Y N N N N M50Propose a method to quantify uncertainty related to traffic data in maritime risk assessment[105] Not defined 2013 N/A R $ (P f n , A, C n 9 U QU ) III Y Y N N N M51 Determine the accident risk of maritime transportation in an inland waterway[106] A risk is composed of two elements: an event or accident occurrence probability and its impact, also known as the consequence severity. (p 96).…”

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confidence: 99%

Maritime transportation risk analysis: Review and analysis in light of some foundational issues

Goerlandt

Montewka

2015

Reliability Engineering & System Safety

262

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a b s t r a c tMany methods and applications for maritime transportation risk analysis have been presented in the literature. In parallel, there is a recent focus on foundational issues in risk analysis, with calls for intensified research on fundamental concepts and principles underlying the scientific field. This paper presents a review and analysis of risk definitions, perspectives and scientific approaches to risk analysis found in the maritime transportation application area, focusing on applications addressing accidental risk of shipping in a sea area. For this purpose, a classification of risk definitions, an overview of elements in risk perspectives and a classification of approaches to risk analysis science are applied. Results reveal that in the application area, risk is strongly tied to probability, both in definitions and perspectives, while alternative views exist. A diffuse situation is also found concerning the scientific approach to risk analysis, with realist, proceduralist and constructivist foundations co-existing. Realist approaches dominate the application area. Very few applications systematically account for uncertainty, neither concerning the evidence base nor in relation to the limitations of the risk model in relation to the space of possible outcomes. Some suggestions are made to improve the current situation, aiming to strengthen the scientific basis for risk analysis.

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confidence: 99%

Maritime transportation risk analysis: Review and analysis in light of some foundational issues

Goerlandt

Montewka

2015

Reliability Engineering & System Safety

262

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“…DST engaged the three basic parameters named basic belief (probability) assignment ( bba ), belief measure (Bel), and plausibility measure (pl) to determine uncertainty in a belief structure in order to aggregate multiexperts' opinions on the basis of their personal degree of belief . Thus, this bba is utilized in this study to collect experts' opinions in the decision‐making problem, in which both local ignorance and global ignorance are well reflected.Definition Suppose Ω is a set of N elements, which is a finite nonempty exhaustive set of mutually exclusive possibilities in the frame of discernment.…”

Section: The Proposed Methodologymentioning

confidence: 99%

Ignorance‐aware safety and reliability analysis: A heuristic approach

Yazdi¹

2019

Quality & Reliability Eng

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In the current study, we aim to solve a group decision‐making problem on the basis of expert judgment with consideration of both global and local ignorance in system safety assessment. When data are acquired from various sources, especially subjective ones, the estimation of the data's precise value is challenging. In such a case, the basic belief assignment (bba) function is utilized to cope with the decision‐making procedure on the basis of Dempster‐Shafer theory (DST). DST, as an effective tool for manipulating inaccurate values, stills is not adequate to obtain the optimum values under the consideration of global and local subjective ignorance. To address the aforementioned subjects in this study, an innovative heuristic approach using a multiobjective programming model is introduced to derive the optimal values (bba) in the system safety assessment. An illustrative example is provided in detail to show the applicability and feasibility of the introduced heuristic approach.

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“…Dempster–Shafer evidence theory (D–S evidence theory) allows for a representation of both imprecision and uncertainty, which derived from a mass function m called BBA . Nowadays, D–S evidence theory has been developing rapidly, and it as an important method that is widely used in many fields such as target recognition, combination clustering, decision analysis, failure detection, and uncertain information . Definition Let Θ={ H 1 , H 2 ,…, H N } be a finite nonempty set of N elements, which is mutually exclusive and exhaustive, and denote P (Θ) as the power set composed of 2 N elements of Θ.…”

Section: Preliminariesmentioning

confidence: 99%

“…method that is widely used in many fields such as target recognition, combination clustering, decision analysis, failure detection, and uncertain information. [29][30][31][32][33][34][35][36] Definition 1 Let ‚ D fH 1 , H 2 , : : : , H N g be a finite nonempty set of N elements, which is mutually exclusive and exhaustive, and denote P.‚/ as the power set composed of 2 N elements of ‚. The BBAs function is defined as a mapping of the power set P.‚/ to a number between 0 and 1, that is, m : P.‚/OE0, 1, and which satisfies the following conditions:…”

Section: Risk Priority Numbermentioning

confidence: 99%

New Failure Mode and Effects Analysis: An Evidential Downscaling Method

et al. 2014

Qual. Reliab. Engng. Int.

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Failure mode and effects analysis (FMEA) is an engineering and management technique, which is widely used to define, identify, and eliminate known or potential failures, problems, errors, and risk from the design, process, service, and so on. In a typical FMEA, the risk evaluation is determined by using the risk priority number (RPN), which is obtained by multiplying the scores of the occurrence, severity, and detection. However, because of the uncertainty in FMEA, the traditional RPN has been criticized because of several shortcomings. In this paper, an evidential downscaling method for risk evaluation in FMEA is proposed. In FMEA model, we utilize evidential reasoning approach to express the assessment from different experts. Multi‐expert assessments are transformed to a crisp value with weighted average method. Then, Euclidean distance from multi‐scale is applied to construct the basic belief assignments in Dempster–Shafer evidence theory application. According to the proposed method, the number of ratings is decreased from 10 to 3, and the frame of discernment is decreased from 210 to 23, which greatly decreases the computational complexity. Dempster's combination rule is utilized to aggregate the assessment of risk factors. We illustrate a numerical example and use the proposed method to deal with the risk priority evaluation in FMEA. The results and comparison show that the proposed method is more flexible and reasonable for real applications. Copyright © 2014 John Wiley & Sons, Ltd.

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Application of Dempster–Shafer theory for the quantification and propagation of the uncertainty caused by the use of AIS data

Cited by 44 publications

References 16 publications

Maritime transportation risk analysis: Review and analysis in light of some foundational issues

Maritime transportation risk analysis: Review and analysis in light of some foundational issues

Ignorance‐aware safety and reliability analysis: A heuristic approach

New Failure Mode and Effects Analysis: An Evidential Downscaling Method

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