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Vessel traffic flow prediction model based on complex network

机译:基于复杂网络的船舶交通流量预测模型

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摘要

A complex network structure can describe many real systems, ports system meet characteristics of complex network system. This paper built a new weighted port evolutional network model using vessel traffic flow as the relevance rating affecting port evolution, on the basis of this. It proposed a port vessel traffic flow forecasting model based on complex networks and used vessel traffic volume of Tianjin Port during 2002-2013 years as the experimental data and ultimately verified and predicted it through the use of forecasting model parameters obtained by fitting port network kinetic equations and numerical, as a result, the error between the experimental results calculated by model and actual data is 4.95%, and the average prediction error during 2009-2013 is less than 2%, the fitting of parameters in this model needed to be supported by historical data, so this model is only applicable in short-term prediction with high accuracy.
机译:复杂的网络结构可以描述许多实际的系统,端口系统满足复杂的网络系统的特征。在此基础上,建立了以船舶流量为影响港口演变的相关性等级的加权港口演化网络模型。提出了基于复杂网络的港口船舶流量预测模型,并以天津港2002-2013年的船舶流量为实验数据,并通过拟合港口网络动力学方程得到的预测模型参数进行了最终验证和预测。数值计算结果表明,模型计算的实验结果与实际数据之间的误差为4.95%,2009-2013年的平均预测误差小于2%,该模型参数的拟合需要得到支持。历史数据,因此该模型仅适用于高精度的短期预测。

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