globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:5852027
论文题名:
考虑周期性波动因素的船舶交通流量预测模型
其他题名: Prediction model of ship traffic flow based on periodic fluctuation factors
作者: 张树奎1; 肖英杰2
刊名: 大连海事大学学报
ISSN: 1006-7736
出版年: 2016
卷: 42, 期:4, 页码:41-46
语种: 中文
中文关键词: 船舶交通流量 ; 周期性波动 ; 线性增长模型 ; 预测
英文关键词: ship traffic flow ; periodic fluctuation ; linear
WOS学科分类: TRANSPORTATION
WOS研究方向: Transportation
中文摘要: 为提高船舶交通流量预测精度,综合考虑季节、气候等因素,通过分析历史流量数据,在线性增长模型的基础上构建了考虑周期性波动因素的船舶交通流量预测改进模型,并运用贝叶斯估计和预测方法求解模型,提出了基于时序数据预测船舶交通流量的预测方法.实例验证表明,较传统线性增长模型,新模型更符合交通流量的实际情况,月流量预测结果的平均绝对误差下降了3.56%,标准差下降了3.79%.因此,新的预测方法用于船舶交通流量预测是有效的.
英文摘要: In order to improve prediction accuracy of ship traffic flow,an improved model was developed to predict ship traffic flow based on linear growth model in consideration of all periodic fluctuation factors,such as season,climate,and so on,then the Bayesian estimation and prediction were used to solve the new model,and ship traffic flow was predicted by using the time series data of ship traffic flow. Results show that the proposed model more accords with the actual situation of traffic flow comparing with the linear growth model,and the mean absolute error of monthly ship flow decreases 3.56%,and the standard deviation decreases 3.79%,therefore,it is effective to predict ship traffic flow.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/157151
Appears in Collections:气候变化事实与影响

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作者单位: 1.江苏海事职业技术学院航海技术学院, 南京, 江苏 211170, 中国
2.上海海事大学商船学院, 上海 201306, 中国

Recommended Citation:
张树奎,肖英杰. 考虑周期性波动因素的船舶交通流量预测模型[J]. 大连海事大学学报,2016-01-01,42(4):41-46
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