Research Article
Provincial Grid Investment Scale Forecasting Based on MLR and RBF Neural Network
Table 5
The average forecasting errors of 23 provinces power grid investment.
| Number | Provinces | Grey model | MLR model average error | MLR-RBF average error |
| 1 | Beijing | 32.28% | 8.74% | | 2 | Tianjin | 35.96% | 0.11% | | 3 | Shanxi | 28.92% | 12.04% | | 4 | Shandong | 25.40% | 10.77% | | 5 | Shanghai | 17.61% | 12.34% | | 6 | Jiangsu | 13.01% | 12.94% | | 7 | Zhejiang | 19.87% | 18.36% | | 8 | Liaoning | 33.60% | 17.98% | | 9 | Anhui | 30.90% | 8.00% | | 10 | Fujian | 15.48 | 16.54% | | 11 | Hubei | | 17.79% | 17.77% | 12 | Hunan | 37.17% | 23.52% | | 13 | Henan | 17.08% | 16.35% | | 14 | Jiangxi | 10.77% | 7.83% | | 15 | Jilin | | 25.21% | 24.89% | 16 | Heilongjiang | 43.68% | 24.36% | | 17 | Shaanxi | 21.56% | 18.96% | | 18 | Sichuan | 41.81% | 22.03% | | 19 | Chongqing | | 23.64% | 23.39% | 20 | Qinghai | 45.26% | 21.21% | | 21 | Ningxia | | 23.73% | 23.36% | 22 | Gansu | 57.53% | 24.27% | | 23 | Xinjiang | 16.58% | 13.39% | |
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