研究文章

参数优化参数Whitenization灰色模型及其应用在模拟和预测在中国高等教育毛入学率

表1

模拟和预测结果的不同模型对中国高等教育毛入学率。

序列号 TWGM (1, - 1 | 0.5, 1) TWGM (1, - 1 | 0.5,r∗) TWGM ( ) TWGM ( )

仿真数据
k= 2 3.5 3.14 10.2188 3.13 10.6725 3.15 10.1019 3.10 11.5502
k= 3 3.9 4.04 3.5078 4.06 4.1620 4.04 3.6783 4.05 3.7288
k= 4 5 4.97 0.6278 5.00 0.0311 4.98 0.4414 4.98 0.4818
k= 5 6 5.94 1.0113 5.96 0.6118 5.95 0.8097 5.93 1.1729
k= 6 7.2 6.95 3.4645 6.96 3.2806 6.97 3.2561 6.92 3.9439
k= 7 8.3 8.00 3.5661 8.00 3.5641 8.02 3.3488 7.94 4.3312
k= 8 9.1 9.10 0.0159 9.09 0.1324 9.12 0.2488 9.01 1.0183
k= 9 9.8 10.24 4.5378 10.22 4.2692 10.27 4.7877 10.12 3.2693
k= 10 10.5 11.44 8.9113 11.40 8.5588 11.46 9.1774 11.28 7.4608
k= 11 12.5 12.68 1.4111 12.63 1.0562 12.71 1.6634 12.50 0.0000
k= 12 13.3 13.97 5.0293 13.92 4.6743 14.00 5.2945 13.77 3.5632
k= 13 15 15.32 2.1024 15.27 1.8063 15.35 2.3637 15.11 0.7258
k= 14 17 16.72 1.6586 16.68 1.8634 16.76 1.4040 16.51 2.8898
k= 15 19 18.18 4.3196 18.16 4.4102 18.23 4.0694 17.98 5.3818
k= 16 21 19.70 6.1832 19.71 6.1376 19.75 5.9357 19.52 7.0515
k= 17 22 21.29 3.2394 21.33 3.0264 21.34 2.9821 21.14 3.9173
k= 18 23 22.94 0.2639 23.04 0.1533 23.00 0.0032 22.84 0.7002
k= 19 23.3 24.66 5.8381 24.82 6.5170 24.73 6.1234 24.63 5.6917

预测数据
k= 20 24.2 26.45 9.3103 26.69 10.2816 26.52 9.6068 26.50 9.5236
k= 21 26.5 28.32 6.8708 28.65 8.1088 28.40 7.1623 28.48 7.4706
k= 22 26.9 30.27 12.5146 30.71 14.1460 30.35 12.8231 30.56 13.5932
k= 23 30. 32.29 7.6443 32.86 9.5415 32.38 7.9409 32.74 9.1365
k= 24 34.5 34.40 0.2759 35.13 1.8131 34.50 0.0000 35.04 1.5616
k= 25 37.5 36.60 2.3881 37.50 0.0000 36.71 2.1169 37.46 0.1167
k= 26 40 38.90 2.7601 39.99 0.0210 39.00 2.4889 40.00 0.0000
k= 27 42.7 41.28 3.3183 42.61 0.2195 41.40 3.0476 42.68 0.0541
k= 28 45.7 43.77 4.2234 45.35 0.7650 43.89 3.9543 45.49 0.4502
k= 29 48.1 46.36 3.6163 48.23 0.2714 46.49 3.3446 48.46 0.7477
k= 30 51.6 49.06 4.9237 51.25 0.6712 49.20 4.6548 51.58 0.0365