中文摘要：

为扩展海上交通系统（MTS）风险的数据样本,更好地开展海上交通系统风险评估研究,有必要研究系统风险仿真中的模型与算法问题。在讨论不确定性信息中随机性和模糊性的基础上,引入云模型来取代概率分布参数下的蒙特卡罗仿真模型。经对无确定度的原始云特征参数求解,获得海上交通系统风险的还原云滴,有效增加海上交通系统风险数据样本,进而分析出风险数值仿真下的海上交通系统风险特征。通过有效性检验,云模型下仿真的变异系数比基于对数正态分布下仿真的结果更稳定。云模型下的仿真结果更准确地逼近原始样本的特性。风险的模糊性和随机性信息量化问题得到解决。

英文摘要：

In order to expand data samples in the MTS and promote the research on systemic risk assessment,it is essential to study the simulation model and numerical algorithm in MTS risk assessment.Cloud model was introduced to simulate risk in place of probability distribution model owing to the existing uncertainty including fuzziness and randomness in risk event.On the basis of the parameters of the original cloud without certainty,droplets of risk cloud in MTS were presented,so as to effectively increase data samples about risk events of MTS.The characteristics of MTS systemic risk were described accurately and analysesd under the condition of risk numerical simulation.After the validation test,the coefficient of variation from the data based on cloud model Monte Carlo simulation was more stable than ones from the simulation by logarithm normal distribution model.The simulation results under the cloud model were more accurately close to the characteristics of the original sample.The problem of quantization of information of fuzziness and randomness about risk was solved.