| 港口船舶交通流量预测 |
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| 引用本文： | 李红喜,付玉慧,张仁初.港口船舶交通流量预测[J].大连海事大学学报(自然科学版),2009,35(3). |
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| 作者姓名： | 李红喜 付玉慧 张仁初 |
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| 作者单位： | 1. 大连海事大学航海学院,辽宁大连,116026
2. 宁波海事局,浙江宁波,315200 |
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| 摘 要： | 为更精确地对港口或航道内船舶交通流量进行预测,分别建立BP神经网络预测模型和RBF神经网络预测模型进行仿真,并以宁波港船舶交通流量为例进行验证.结果表明,在宁波港现有发展基础和港口设施状况下,RBF神经网络用于宁波港船舶交通流量预测误差较小,预测值与实际值相近.
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| 关 键 词： | 船舶交通流量 预测模型 神经网络 |
Ship traffic volume forecasting in port |
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| LI Hong-xi
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FU Yu-hui
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ZHANG Ren-chu.Ship traffic volume forecasting in port[J].Journal of Dalian Maritime University,2009,35(3). |
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| Authors: | LI Hong-xi FU Yu-hui ZHANG Ren-chu |
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| Institution: | LI Hong-xi1,FU Yu-hui1,ZHANG Ren-chu2(1.Navigation College,Dalian Maritime University,Dalian 116026,China,2.Ningbo Maritime Safety Administration,Ningbo 315200,China) |
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| Abstract: | To forecast ship traffic volume in port or waterway precisely,back propagation(BP) and radial basis function(RBF) neural network forecasting models were established and simulated.Tests in Ningbo port show that RBF neural network has the smaller error in forecasting ship traffic volume,and the predictive value is close to actual one under the current basis and port facilities. |
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| Keywords: | ship traffic volume forecasting model neural networks |
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