刘夏, 李苑辉, 欧志鹏, 陈磊, 陈明锐.基于ARIMA与灰色马尔科夫模型的三亚市交通客流量预测研究[J].重庆工商大学自然科学版,2019,36(5):82-88
基于ARIMA与灰色马尔科夫模型的三亚市交通客流量预测研究
Research on Traffic Passenger Flow Prediction of Sanya City Based on ARIMA and Grey Markov Models
  
DOI:
中文关键词:  ARIMA模型  灰色预测  灰色马尔科夫模型  交通客流  预测
英文关键词:ARIMA model, grey prediction, grey Markov model, passenger volume, prediction
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作者单位
刘夏, 李苑辉, 欧志鹏, 陈磊, 陈明锐 1.三亚航空旅游职业学院,海南 三亚 5720002.海南大学 计算机与网络空间安全学院,海口 570228 
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中文摘要:
      为了较为全面、客观、准确地预测城市的交通客流量,对三亚市旅游统计数据2012-2017年每月的交通客流数据进行分析,在数据整理的基础上,主要采用ARIMA模型和灰色马尔科夫模型对2012-01—2017-12月三亚的交通流量分别进行拟合仿真,并对2018年每月的客流进行了趋势外推预测;结果表明:采用ARIMA预测模型所获得的平均绝对百分误差为4.42%,采用灰色马尔科夫模型获得的平均绝对百分误差为3.78%,表明两种预测具有较高的精度;最后利用灰色马尔科夫模型进行趋势外推预测,得出三亚市2018年交通客流预计近3 600万,预测结果对三亚市旅游、交通等行业制定政策能起到积极的作用。
英文摘要:
      In order to predict the traffic flow of the city comprehensively, objectively and accurately, the monthly traffic flow data of Sanya from 2012 to 2017 were collected for analysis.On the basis of data collation, ARIMA model and gray Markov model are mainly adopted to carry out fitting simulation for the traffic flow of Sanya from January,2012 to December,2017, and to extrapolate the passenger flow trend of each month in 2018.The results show that the average absolute percentage error of ARIMA prediction model is 4.42%, and the average absolute percentage error of Markov model is 3.78%,which indicate that the prediltion by the two models has high precision.Finally, the trend extrapolation is predicted by using the gray Markov model, and the traffic flow in Sanya in 2018 is estimated to be nearly 36 million.The predicted results can play a positive role in the formulation of policies in the tourism, transportation and other industries in Sanya.
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