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Risk prediction of marine traffic based on Fractal interpolation algorithm

机译:基于分形插值算法的海上交通风险预测

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Risk prediction is the key element in risk managements. The commonly quantitative prediction methods approaches focus on reasoning by statistics data. This paper held out the Fractal interpolation algorithm to solve the time series data by means of transferring the discrete data to continue data. On the basis of introduction of fractal theory applying the feasibility to marine traffic accidents, it is presented by evaluating iterated function system and its attractor, which uses fractal interpolation algorithm to handle discrete data aggregating with time series, and then models the risk prediction of marine accidents theoretically. Finally, taking statistic data of marine traffic accidents as case studies, it proves that the data reasoning model is more accurate than common computing algorithm special for high fluctuant curve.
机译:风险预测是​​风险管理中的关键要素。通常的定量预测方法集中于通过统计数据进行推理。本文提出了分形插值算法,通过将离散数据转换为连续数据来求解时间序列数据。在介绍适用于海上交通事故的分形理论的基础上,通过对迭代函数系统及其吸引子的评估,提出了分形理论,利用分形插值算法处理离散的时间序列数据,然后对海洋风险进行建模。理论上发生意外。最后,以海上交通事故统计数据为例,证明了该数据推理模型比常用的高波动曲线专用计算算法更为准确。

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