Risk Assessment of Traffic Environment at Port Using Unascertained Measure Model

机译：基于不确定模型的港口交通环境风险评估

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The risk of port areas is an issue to express the uncertain information. Among this uncertain information, besides incomplete information of objective conditions, there are also of policymaker's intension and experience. In order to assess the traffic risk of port, the theories and methods of unascertained mathematics based on entropy were introduced. Considering the unascertained characteristics of port traffic environment, the weight of assessment indicators was determined and an unascertained quantitative model was established for port traffic evaluation on the basis of the information entropy theory. Then, we get the corresponding rank and evaluation of the risk, with the help of applying this model in 13 sections of two ports of China. Compared with traditional weight confirmed method, the results show that the evaluation is reliable, and this unascertained measure is more propitious to resolve the evaluation of traffic risk in different ports by the same evaluation standard.

机译：港口地区的风险是表达不确定信息的问题。在这些不确定的信息中，除了客观条件的信息不完整之外，还有决策者的意图和经验。为了评估港口的交通风险，介绍了基于熵的不确定数学的理论和方法。考虑到港口交通环境不确定的特征，基于信息熵理论，确定了评价指标的权重，建立了港口交通评价不确定的量化模型。然后，借助于在中国两个港口的13个区域中应用此模型，我们得到了相应的风险等级和评估。结果表明，与传统的权重确定方法相比，该方法是可靠的，这种不确定的方法更有利于用相同的评价标准解决不同港口的交通风险评价。

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来源
《The 2nd International Conference on Risk Analysis and Crisis Response(第二届风险分析与危机反应国际学术研讨会)》|2009年|466-472|共7页
会议地点 Beijing(CN);Beijing(CN)
作者
LI Wei; HU Shenping; YOU Qinghua; XI Yongtao;
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作者单位

Merchant Marine College, Shanghai Maritime University, Shanghai 200135, China;

Merchant Marine College, Shanghai Maritime University, Shanghai 200135, China;

Merchant Marine College,Shanghai Maritime University, Shanghai 200135, China;

Merchant Marine College, Shanghai Maritime University, Shanghai 200135, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
ship; traffic environment; unascertained measure; entropy; risk assessment;

机译：船舶;交通环境;不确定措施;熵;风险评估;

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Risk Assessment of Traffic Environment at Port Using Unascertained Measure Model

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