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Analysis and Prediction of Water Traffic Accidents in Jingtang Port based on Improved GM(1,1) Model

机译:基于改进GM(1,1)模型的京唐港水上交通事故分析与预测

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The prediction of water traffic accidents is important for port safety management. There are various influential factors for the water traffic which presents challenges for the prediction of water traffic accident. The traditional grey model (GM) gained much popularity in prediction applications, but the prediction accuracy is not satisfactory for the complex nonlinear system. In this paper, the GM is improved by tuning generation coefficients of the traditional model to better tracking the changing tendency of the system. The improved model is validated by water traffic accident prediction simulations based on the accident statistics of Jingtang Port in Tangshan in the last seven years. The results show that different prediction sequences correspond to different values of generation coefficient, which can get high -precision level predictions. The simulation results demonstrated the effectiveness and efficiency of the proposed improved GM(1,1) model.
机译:水上交通事故的预测对于港口安全管理非常重要。水运影响因素多种多样,对水运事故的预测提出了挑战。传统的灰色模型(GM)在预测应用中获得了很大的普及,但是对于复杂的非线性系统,其预测精度并不令人满意。在本文中,通过调整传统模型的生成系数来改进GM,以更好地跟踪系统的变化趋势。基于唐山京唐港近七年的事故统计数据,通过水上交通事故预测模拟对改进后的模型进行了验证。结果表明,不同的预测序列对应不同的生成系数值,可以得到高精度的预测结果。仿真结果证明了改进的GM(1,1)模型的有效性和效率。

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