地理科学 ›› 2017, Vol. 37 ›› Issue (2): 209-216.doi: 10.13249/j.cnki.sgs.2017.02.006
所属专题: 地理大数据
收稿日期:
2016-02-25
修回日期:
2016-08-05
出版日期:
2017-02-25
发布日期:
2017-02-25
作者简介:
作者简介:李欣(1981-),男,河南郑州人,博士,讲师,主要从事地理信息系统理论研究与实践应用研究。E-mail:
基金资助:
Received:
2016-02-25
Revised:
2016-08-05
Online:
2017-02-25
Published:
2017-02-25
Supported by:
摘要:
针对城市道路拥堵问题的日益加剧的问题,智能化城市交通管理平台是缓解拥堵问题的有效方法,利用交通流大数据预测结果进行交通诱导,能够指导用户调整出行方案,有效缓解交通压力。研究了交通流大数据的分布式增量聚合方法,对海量交通流数据进行清洗统计,为交通流预测提供数据基础,基于交通流在路网中上下游路段的相关性分析,利用路口转弯率多阶分配将该相关性量化,构建基于路网相关性的空间权重矩阵,完成对于STARIMA模型的改进。通过应用试验证明,该方法能更准确的进行交通流预测,为交通诱导信息发布提供依据。
中图分类号:
李欣, 孟德友. 基于路网相关性的分布式增量交通流大数据预测方法[J]. 地理科学, 2017, 37(2): 209-216.
Xin Li, Deyou Meng. Distributed Incremental Traffic Flow Big Data Forecasting Method Based on Road Network Correlation[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(2): 209-216.
表1
两种方法预测结果均方误差(MSE)对比"
编号 | 动态 STARIMA | 路网相关STARIMA | 编号 | 动态 STARIMA | 路网相关STARIMA | 编号 | 动态 STARIMA | 路网相关STARIMA |
---|---|---|---|---|---|---|---|---|
1 | 8638.27 | 6643.68 | 22 | 3338.29 | 2839.48 | 43 | 3977.67 | 3058.83 |
2 | 7396.01 | 6032.39 | 23 | 6236.77 | 5064.66 | 44 | 4458.98 | 3847.45 |
3 | 6631.31 | 4983.57 | 24 | 7784.39 | 5338.54 | 45 | 8979.37 | 7432.82 |
4 | 8362.58 | 5986.44 | 25 | 2526.67 | 1438.33 | 46 | 8443.69 | 6234.73 |
5 | 2948.21 | 1863.49 | 26 | 3464.32 | 1974.34 | 47 | 2798.55 | 1846.49 |
6 | 4820.22 | 2799.35 | 27 | 8764.39 | 5890.43 | 48 | 3985.42 | 2275.45 |
7 | 9230.23 | 7390.32 | 28 | 6549.48 | 5438.93 | 49 | 7849.43 | 5893.37 |
8 | 7857.46 | 6074.45 | 29 | 12974.45 | 8865.29 | 50 | 6692.38 | 5624.78 |
9 | 15324.01 | 12984.61 | 30 | 13084.44 | 10474.63 | 51 | 6639.32 | 4542.43 |
10 | 11479.46 | 8753.05 | 31 | 5478.34 | 3740.35 | 52 | 5873.57 | 4147.57 |
11 | 3892.27 | 2775.73 | 32 | 4858.34 | 3275.39 | 53 | 3720.32 | 2475.54 |
12 | 4917.48 | 3295.48 | 33 | 7434.95 | 6578.36 | 54 | 3920.28 | 2143.27 |
13 | 3729.33 | 2903.57 | 34 | 7868.23 | 5920.49 | 55 | 2039.58 | 1343.47 |
14 | 3928.23 | 2638.57 | 35 | 6743.23 | 4839.33 | 56 | 3235.62 | 1634.57 |
15 | 4478.19 | 3902.29 | 36 | 7820.33 | 5923.67 | 57 | 4838.88 | 3822.44 |
16 | 6903.36 | 4632.84 | 37 | 8068.35 | 6488.38 | 58 | 5749.23 | 4727.28 |
17 | 10573.48 | 7296.23 | 38 | 7819.28 | 6367.35 | 59 | 6403.45 | 4884.74 |
18 | 9033.54 | 7018.83 | 39 | 3894.22 | 2057.75 | 60 | 6653.63 | 4954.54 |
19 | 4847.34 | 3892.33 | 40 | 4780.44 | 3628.65 | 61 | 7570.49 | 6343.45 |
20 | 3309.21 | 3087.88 | 41 | 7897.36 | 4929.38 | 62 | 8788.48 | 6932.43 |
21 | 5789.22 | 4274.49 | 42 | 8902.34 | 5563.37 |
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