Vessel traffic flow prediction model based on complex network

Wen Hang, Mengyuan Xu, Xingyuan Chen, Shaolong Zhou
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引用次数: 1

Abstract

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.
基于复杂网络的船舶交通流预测模型
一个复杂的网络结构可以描述许多实际系统,端口系统符合复杂网络系统的特点。在此基础上,以船舶交通流为影响港口演化的关联等级,构建了一个新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交通流量预测模型,并以天津港2002-2013年的船舶交通量为实验数据,通过拟合港口网络动力学方程和数值计算得到预测模型参数,最终对模型进行了验证和预测,模型计算的实验结果与实际数据的误差为4.95%。2009-2013年的平均预测误差小于2%,模型中参数的拟合需要历史数据的支持,因此该模型仅适用于短期预测,且精度较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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