| 基于支持向量机的船舶交通流量预测模型 |
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| 引用本文： | 冯宏祥,肖英杰,孔凡邨.基于支持向量机的船舶交通流量预测模型[J].中国航海,2011,34(4). |
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| 作者姓名： | 冯宏祥 肖英杰 孔凡邨 |
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| 作者单位： | 上海海事大学航运仿真技术教育部工程研究中心,上海,200135 |
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| 基金项目： | 上海市科委2009年度创新行动计划项目，上海海事大学校基金 |
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| 摘 要： | 针对船舶交通流的随机性大,影响因素多,船舶交通流量预测的准确度不高等现象,基于支持向量机理论,结合长江苏通大桥断面的观测数据,建立支持向量机的预测模型进行短期的船舶流量预测.预测结果与实际流量比较一致,优于SPSS线性回归的预测效果.验证了支持向量机预测模型在船舶流量短期预测中的可行性.
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| 关 键 词： | 水路运输 支持向量机 船舶交通流量 预测 回归分析 |
Study of Vessel Traffic Forecasting Model Based on Support Vector Machine |
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| Feng Hongxiang,Xiao Yingjie,Kong Fancun.Study of Vessel Traffic Forecasting Model Based on Support Vector Machine[J].Navigation of China,2011,34(4). |
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| Authors: | Feng Hongxiang Xiao Yingjie Kong Fancun |
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| Institution: | Feng Hongxiang,Xiao Yingjie,Kong Fancun(Merchant Marine College,Shanghai Maritime University,Shanghai 200135,China) |
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| Abstract: | Based on vessel traffic data and Support Vector Machine theory,a SVM model to predict short term vessel traffic is presented.Forecasted vessel traffic by the model coincides with observations of actual traffic,with mean absolute percentage error smaller than that by SPSS regression model.The fact validates the feasibility of the SVM forecasting model in vessel traffic forecasting. |
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| Keywords: | waterway transportation support vector machine(SVM) vessel traffic forecasting regression analysis |
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