基于路网相关性的分布式增量交通流大数据预测方法

李欣, 孟德友

Distributed Incremental Traffic Flow Big Data Forecasting Method Based on Road Network Correlation

Xin Li, Deyou Meng

表1 两种方法预测结果均方误差（MSE）对比

Table 1 The MSE comparison of two predict methods results

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