An approach of vessel collision risk assessment based on the D–S evidence theory

Li, Bo; Pang, Fuwen

doi:10.1016/j.oceaneng.2013.09.016

Cited by 102 publications

(48 citation statements)

References 16 publications

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“…Si et al proposed a novel prediction approach through information fusion of improved D-S evidence theory and neural network to forecast the distribution of coal seam terrain [6]. Li and Pang use D-S evidence theory to solve vessel collision risk assessment [7]. Experimental results show that the proposed approach confirms the validity and is reasonable for real application.…”

Section: Introductionmentioning

confidence: 82%

Ship Electric Propulsion Simulation System Reliability Evaluation Based on Improved D-S Expert Weight Calculation Method

Xing

et al. 2015

Mathematical Problems in Engineering

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In order to have a better evaluation process to determine the experts weight in the evaluation process, this paper proposes a new expert weight calculation method. First of all to establish electric propulsion simulation evaluation system, use AHP method to calculate the initial weight principle of index. Then use the D-S to fuse the experts evaluation information, combined with the weight vector, structure of the expert weight objective function, and through the genetic algorithm to solve the expert weight size. According to the expert weight vector, calculate the final weight vector. Not only can it greatly make use of the experts information and analyze the similarity of information effectively but also it calculates the weight of each expert objectively. At the same time the evaluation subjective factors have been reduced by the adoption of this new method.

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Section: Introductionmentioning

confidence: 82%

Ship Electric Propulsion Simulation System Reliability Evaluation Based on Improved D-S Expert Weight Calculation Method

Xing

et al. 2015

Mathematical Problems in Engineering

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“…The most practical one is the Dempster-Shafer combinational rule, which can fuse lots of uncertain evidence from different sources so as to improve the accuracy of the reasoning for the event [5].…”

Section: Brief Overview On the Algorithm Of D-s Theorymentioning

confidence: 99%

Risk Assessment of Agricultural Products Supply-Chain Finance Based on D-S Theory

Zhang¹,

Duan²,

Ge-fu³

2014

AJCM

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Agricultural products supply-chain finance, as one of the solutions to the issue of "capital problems" of agriculture, countryside and farmers, has proposed a kind of characteristics model to assess the risk of agricultural production, processing and marketing, which can improve the issue of farmers and enterprises lacking of funds. This model is proposed on the basis of uncertain information processing method of D-S theory and its data combination rules, combined with the "discount rate" correction model, and it includes a risk assessment index system of agricultural products supply-chain finance, fully considering the five aspects of production, processing, marketing, cooperation of supply chain and collateral. At last, a taro supply chain is taken for example. And the risk assessment of its supply-chain finance based on this model has been discussed in detail. And the result has proved that the model and its algorithm are practical and feasible.

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“…As we know, the Dempster-Shafer (D-S) evidence theory is an appropriate approach to combine the multi-information. 16,17 With the dependent basic probabilistic assignment (BPA), the alternative technique for combining evidences was introduced in Blasch et al 18 Subsequently, Zadeh showed that the use of normalization factor of D-S combination rule on highly conflicting evidence could lead to the counterintuitive results in some cases. 19 On the other hand, the fuzzy logic has its own advantage on the intelligent decision-making, whose solution can be cast in terms that are readily understood.…”

Section: Introductionmentioning

confidence: 99%

Navigation risk assessment scheme based on fuzzy Dempster–Shafer evidence theory

2018

International Journal of Advanced Robotic Systems

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In order to reduce the influence of subjective factors on navigation risk assessment, we present a novel scheme based on the fuzzy Dempster-Shafer evidence theory in this article. At first, we deduce the fuzzy set after analyzing various indicators in actual vessel navigation as an example. What's more, the current data can be adaptively transformed into quantitative information on the basis of two-order membership functions. Considering the inherent defects of standard Dempster-Shafer evidence framework, the assessment process is improved to combine the uncertain and conflicting evidences from available indicators to make reliable decision. Further, three propositions are derived to explain the proposed scheme step by step. Finally, the numerical study results indicate that the proposed scheme has satisfactory performance for vessel navigation risk assessment in the complex waters without any subjective factors.

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An approach of vessel collision risk assessment based on the D–S evidence theory

Cited by 102 publications

References 16 publications

Ship Electric Propulsion Simulation System Reliability Evaluation Based on Improved D-S Expert Weight Calculation Method

Ship Electric Propulsion Simulation System Reliability Evaluation Based on Improved D-S Expert Weight Calculation Method

Risk Assessment of Agricultural Products Supply-Chain Finance Based on D-S Theory

Navigation risk assessment scheme based on fuzzy Dempster–Shafer evidence theory

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