| 基于IOWA算子的水上交通事故组合预测模型 |
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| 引用本文： | 王当利,吕雪,王雪佳,高如江.基于IOWA算子的水上交通事故组合预测模型[J].上海海事大学学报,2018,39(3):34-40. |
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| 作者姓名： | 王当利 吕雪 王雪佳 高如江 |
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| 作者单位： | 武汉理工大学航运学院;武汉理工大学内河航运技术湖北省重点实验室;中交上海航道勘察设计研究院有限公司 |
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| 摘 要： | 为提高水上交通事故的预测精度,将引入弱化算子序列的灰色模型和支持向量回归模型的预测结果进行组合,进而构建基于IOWA算子的组合预测模型。以全国和长江某流域水上交通事故历史数据为预测样本,将组合预测模型的预测结果与其他预测模型的预测结果进行对比。结果显示:组合预测模型的预测精度更高,能更好地反映水上交通事故的发展趋势。
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| 关 键 词： | 事故预测 灰色模型 支持向量机 IOWA算子 |
| 收稿时间： | 2017/9/27 0:00:00 |
| 修稿时间： | 2017/11/27 0:00:00 |
Combined prediction model of waterway traffic accidents based on IOWA operator |
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| Institution: | School of Navigation, Wuhan University of Technology,School of Navigation, Wuhan University of Technology,School of Navigation, Wuhan University of Technology |
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| Abstract: | In order to improve the prediction accuracy of waterway traffic accidents, the prediction results of the grey model based on weakening operator sequence and the support vector regression model are combined, and a combined prediction model based on the IOWA operator is constructed. Based on the historical data of waterway traffic accidents in China and a certain basin of the Yangtze River, the prediction results of the combined prediction model are compared with those of other prediction models. The results show that the combined prediction model is of higher prediction accuracy and can better reflect the development trend of waterway traffic accidents. |
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| Keywords: | accident prediction grey model support vector machine IOWA operator |
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